5,163 results on '"Wilcox A"'
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2. Interactions between atmospheric composition and climate change – Progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
- Author
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Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, Forster, Piers M., Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, and Forster, Piers M.
- Abstract
The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood and diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation-response paradigm through multi-model ensembles of Earth System Models of varying complexity. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible, and machine learning approaches for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that lever
- Published
- 2024
- Full Text
- View/download PDF
3. Interactions between atmospheric composition and climate change – Progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
- Author
-
Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, Forster, Piers M., Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, and Forster, Piers M.
- Abstract
The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood and diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation-response paradigm through multi-model ensembles of Earth System Models of varying complexity. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible, and machine learning approaches for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that lever
- Published
- 2024
- Full Text
- View/download PDF
4. Interactions between atmospheric composition and climate change – Progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
- Author
-
Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, Forster, Piers M., Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, and Forster, Piers M.
- Abstract
The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood and diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation-response paradigm through multi-model ensembles of Earth System Models of varying complexity. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible, and machine learning approaches for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that lever
- Published
- 2024
- Full Text
- View/download PDF
5. Advancing specificity in delirium: The delirium subtyping initiative
- Author
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AIOS Psychiatrie, Brain, Affectieve & Psychotische Med., Bowman, Emily M L, Brummel, Nathan E, Caplan, Gideon A, Cunningham, Colm, Evered, Lis A, Fiest, Kirsten M, Girard, Timothy D, Jackson, Thomas A, LaHue, Sara C, Lindroth, Heidi L, Maclullich, Alasdair M J, McAuley, Daniel F, Oh, Esther S, Oldham, Mark A, Page, Valerie J, Pandharipande, Pratik P, Potter, Kelly M, Sinha, Pratik, Slooter, Arjen J C, Sweeney, Aoife M, Tieges, Zoë, Van Dellen, Edwin, Wilcox, Mary Elizabeth, Zetterberg, Henrik, Cunningham, Emma L, AIOS Psychiatrie, Brain, Affectieve & Psychotische Med., Bowman, Emily M L, Brummel, Nathan E, Caplan, Gideon A, Cunningham, Colm, Evered, Lis A, Fiest, Kirsten M, Girard, Timothy D, Jackson, Thomas A, LaHue, Sara C, Lindroth, Heidi L, Maclullich, Alasdair M J, McAuley, Daniel F, Oh, Esther S, Oldham, Mark A, Page, Valerie J, Pandharipande, Pratik P, Potter, Kelly M, Sinha, Pratik, Slooter, Arjen J C, Sweeney, Aoife M, Tieges, Zoë, Van Dellen, Edwin, Wilcox, Mary Elizabeth, Zetterberg, Henrik, and Cunningham, Emma L
- Published
- 2024
6. Dynamic acetabular cup orientation during gait: a study of fast and slow walking total hip replacement patients
- Author
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Vasiljeva, Ksenija, Lunn, David, Chapman, Graham, Redmond, Anthony, Wang, Lin, Thompson, Jonathan, Williams, Sophie, Wilcox, Ruth, Jones, Alison, Vasiljeva, Ksenija, Lunn, David, Chapman, Graham, Redmond, Anthony, Wang, Lin, Thompson, Jonathan, Williams, Sophie, Wilcox, Ruth, and Jones, Alison
- Abstract
The dynamic orientation of total hip replacement acetabular cups during walking may vary sub-stantially from their assumed position at surgical implantation and may vary between individuals. The scale of this effect is of interest for both pre-clinical device testing and for pre-operative sur-gical planning. This work aimed to evaluate: 1) patient variation in dynamic cup orientation; 2) whether walking speed was a candidate proxy measure for the dynamic cup orientation; and 3) the relationships between dynamic cup orientation angles and planar pelvic angles. Pelvic movement data for patients with fast (n=20) and slow (n=19) self-selected walking speeds, was used to calcu-late acetabular cup inclination and version angles through gait. For aim 1, the range and extremes of acetabular cup orientation angles were analysed for all patients. Large patient to patient varia-tion was found in the range of both inclination angle (1° to 11°) and version angle (4° to 18°). The version angle was typically retroverted in comparison to the implantation position (greatest devi-ation 27o). This orientation is substantially different to the static, 0° version simplifying assump-tions in pre-clinical ‘edge loading’ testing. For aim 2, the cup orientation angles were compared between the fast and slow walking groups using statistical parametric mapping. The only signifi-cant differences observed were for cup version angle, for ~12% of the gait cycle, before toe-off (p < 0.05). Therefore, self-selected walking speed, in isolation, is not a sufficient proxy measure for dynamic acetabular orientation. For aim 3, correlations were recorded between the acetabular cup orientation angles and the planar pelvic angles. The cup inclination angle during gait was strongly correlated (Spearman’s coefficient -1) with pelvic obliquity alone, indicating that simple planar assessment could be used to anticipate range of inclination angle. The cup version angle was cor-related with both pelvic rotation
- Published
- 2024
7. Compact Housing for Incremental Growth: The K206 RDP Project in Alexandra, Johannesburg
- Author
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Wilcox, A.Y. (author), Mota, Nelson (author), Haffner, M.E.A. (author), Elsinga, M.G. (author), Wilcox, A.Y. (author), Mota, Nelson (author), Haffner, M.E.A. (author), and Elsinga, M.G. (author)
- Abstract
The South African Reconstruction and Development Programme (RDP) was initiated to provide subsidised housing for low‐income families. However, the programme faced challenges in establishing adequate technical guidelines and standards, resulting in subpar housing quality. This article discusses the multifaceted nature of subsidised housing design, emphasising the importance of incorporating technical housing standards as well as the spatial needs of residents based on their context (at both domestic and neighbourhood scales). The article focuses on the K206 housing RDP project in Alexandra, Johannesburg, as a case study that transitioned from generic technical standards to a resident‐responsive design scheme that was inspired by the backyard room incremental expansions that were already prevalent in the Alexandra context. A critical review of South Africa’s RDP housing design technical standards and policy is explored. The article also examines the density standards and allowances for incremental expansions introduced by the K206 project, analysing data derived from fieldwork observations, interviews, and the spatial analysis of 26 dwelling units. The study’s findings underscore the significance of maintaining an equilibrium between technical standards and resident‐responsive design decisions. The results demonstrate that tailoring the RDP housing design solutions to unique contextual needs can significantly elevate the quality of life of residents concerning income generation and flexibility for incremental expansion. However, this balance is delicate and disparities between the RDP technical standards and user‐initiated development over time also have the potential to ultimately impair residents’ living spaces., Urban Development Management, Space & Type
- Published
- 2024
- Full Text
- View/download PDF
8. Undescended testis:A roundtable discussion based on clinical scenarios - Part 1
- Author
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Baydilli, Numan, Dönmez, M. İrfan, Wilcox, Duncan T., Hadziselimovic, Faruk, Hayashi, Yutaro, Oswald, Josef, Ziylan, Orhan, Thorup, Jorgen, Kapelari, Klaus, Soygür, Tarkan, Favorito, Luciano Alves, Braga, Luis H., 't Hoen, Lisette A., O'Kelly, Fardod, Sforza, Simone, Lammers, Rianne, Bindi, Edoardo, Paraboschi, Irene, Haid, Bernhard, Madarriaga, Yesica Quiroz, Banuelos Marco, Beatriz, Baydilli, Numan, Dönmez, M. İrfan, Wilcox, Duncan T., Hadziselimovic, Faruk, Hayashi, Yutaro, Oswald, Josef, Ziylan, Orhan, Thorup, Jorgen, Kapelari, Klaus, Soygür, Tarkan, Favorito, Luciano Alves, Braga, Luis H., 't Hoen, Lisette A., O'Kelly, Fardod, Sforza, Simone, Lammers, Rianne, Bindi, Edoardo, Paraboschi, Irene, Haid, Bernhard, Madarriaga, Yesica Quiroz, and Banuelos Marco, Beatriz
- Abstract
Undescended testis (UDT, cryptorchidism) is the most common congenital anomaly of the genital tract. Despite its high incidence, the management of UDT varies between specialties (urology, pediatric surgery, pediatric urology, pediatric endocrinology). Therefore, as the European Association of Urology - Young Academic Urologists Pediatric Urology Working Group, we requested experts around the world to express their own personal approaches against various case scenarios of UDT in order to explore their individual reasoning. We intended to broaden the perspectives of our colleagues who deal with the treatment of this frequent genital malformation.
- Published
- 2024
9. Is Simultaneous Binding to DNA and Gyrase Important for the Antibacterial Activity of Cystobactamids?
- Author
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Solga, Danny, Wieske, Hermina, Wilcox, Scott, Zeilinger, Carsten, Jansen-Olliges, Linda, Cirnski, Katarina, Herrmann, Jennifer, Mueller, Rolf, Erdélyi, Máté, Kirschning, Andreas, Solga, Danny, Wieske, Hermina, Wilcox, Scott, Zeilinger, Carsten, Jansen-Olliges, Linda, Cirnski, Katarina, Herrmann, Jennifer, Mueller, Rolf, Erdélyi, Máté, and Kirschning, Andreas
- Abstract
Cystobactamids are aromatic oligoamides that exert their natural antibacterial properties by inhibition of bacterial gyrases. Such aromatic oligoamides were proposed to inhibit alpha-helix-mediated protein-protein interactions and may serve for specific recognition of DNA. Based on this suggestion, we designed new derivatives that have duplicated cystobactamid triarene units as model systems to decipher the specific binding mode of cystobactamids to double stranded DNA. Solution NMR analyses revealed that natural cystobactamids as well as their elongated analogues show an overall bent shape at their central aliphatic unit, with an average CX-CY-CZ angle of similar to 110 degrees. Our finding is corroborated by the target-bound structure of close analogues, as established by cryo-EM very recently. Cystobactamid CN-861-2 binds directly to the bacterial gyrase with an affinity of 9 mu M, and also exhibits DNA-binding properties with specificity for AT-rich DNA. Elongation/dimerization of the triarene subunit of native cystobactamids is demonstrated to lead to an increase in DNA binding affinity. This implies that cystobactamids' gyrase inhibitory activity necessitates not just interaction with the gyrase itself, but also with DNA via their triarene unit.
- Published
- 2024
- Full Text
- View/download PDF
10. Dynamic acetabular cup orientation during gait: a study of fast and slow walking total hip replacement patients
- Author
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Vasiljeva, Ksenija, Lunn, David, Chapman, Graham, Redmond, Anthony, Wang, Lin, Thompson, Jonathan, Williams, Sophie, Wilcox, Ruth, Jones, Alison, Vasiljeva, Ksenija, Lunn, David, Chapman, Graham, Redmond, Anthony, Wang, Lin, Thompson, Jonathan, Williams, Sophie, Wilcox, Ruth, and Jones, Alison
- Abstract
The dynamic orientation of total hip replacement acetabular cups during walking may vary sub-stantially from their assumed position at surgical implantation and may vary between individuals. The scale of this effect is of interest for both pre-clinical device testing and for pre-operative sur-gical planning. This work aimed to evaluate: 1) patient variation in dynamic cup orientation; 2) whether walking speed was a candidate proxy measure for the dynamic cup orientation; and 3) the relationships between dynamic cup orientation angles and planar pelvic angles. Pelvic movement data for patients with fast (n=20) and slow (n=19) self-selected walking speeds, was used to calcu-late acetabular cup inclination and version angles through gait. For aim 1, the range and extremes of acetabular cup orientation angles were analysed for all patients. Large patient to patient varia-tion was found in the range of both inclination angle (1° to 11°) and version angle (4° to 18°). The version angle was typically retroverted in comparison to the implantation position (greatest devi-ation 27o). This orientation is substantially different to the static, 0° version simplifying assump-tions in pre-clinical ‘edge loading’ testing. For aim 2, the cup orientation angles were compared between the fast and slow walking groups using statistical parametric mapping. The only signifi-cant differences observed were for cup version angle, for ~12% of the gait cycle, before toe-off (p < 0.05). Therefore, self-selected walking speed, in isolation, is not a sufficient proxy measure for dynamic acetabular orientation. For aim 3, correlations were recorded between the acetabular cup orientation angles and the planar pelvic angles. The cup inclination angle during gait was strongly correlated (Spearman’s coefficient -1) with pelvic obliquity alone, indicating that simple planar assessment could be used to anticipate range of inclination angle. The cup version angle was cor-related with both pelvic rotation
- Published
- 2024
11. Implications of Regulations on the Use of AI and Generative AI for Human-Centered Responsible Artificial Intelligence
- Author
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Constantinides, Marios, Tahaei, Mohammad, Quercia, Daniele, Stumpf, Simone, Madaio, Michael, Kennedy, Sean, Wilcox, Lauren, Vitak, Jessica, Cramer, Henriette, Bogucka, Edyta, Baeza-Yates, Ricardo, Luger, Ewa, Holbrook, Jess, Muller, Michael, Blumenfeld, Ilana Golbin, Pistilli, Giada, Constantinides, Marios, Tahaei, Mohammad, Quercia, Daniele, Stumpf, Simone, Madaio, Michael, Kennedy, Sean, Wilcox, Lauren, Vitak, Jessica, Cramer, Henriette, Bogucka, Edyta, Baeza-Yates, Ricardo, Luger, Ewa, Holbrook, Jess, Muller, Michael, Blumenfeld, Ilana Golbin, and Pistilli, Giada
- Abstract
With the upcoming AI regulations (e.g., EU AI Act) and rapid advancements in generative AI, new challenges emerge in the area of Human-Centered Responsible Artificial Intelligence (HCR-AI). As AI becomes more ubiquitous, questions around decision-making authority, human oversight, accountability, sustainability, and the ethical and legal responsibilities of AI and their creators become paramount. Addressing these questions requires a collaborative approach. By involving stakeholders from various disciplines in the 2\textsuperscript{nd} edition of the HCR-AI Special Interest Group (SIG) at CHI 2024, we aim to discuss the implications of regulations in HCI research, develop new theories, evaluation frameworks, and methods to navigate the complex nature of AI ethics, steering AI development in a direction that is beneficial and sustainable for all of humanity., Comment: 6 pages
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- 2024
12. Farsight: Fostering Responsible AI Awareness During AI Application Prototyping
- Author
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Wang, Zijie J., Kulkarni, Chinmay, Wilcox, Lauren, Terry, Michael, Madaio, Michael, Wang, Zijie J., Kulkarni, Chinmay, Wilcox, Lauren, Terry, Michael, and Madaio, Michael
- Abstract
Prompt-based interfaces for Large Language Models (LLMs) have made prototyping and building AI-powered applications easier than ever before. However, identifying potential harms that may arise from AI applications remains a challenge, particularly during prompt-based prototyping. To address this, we present Farsight, a novel in situ interactive tool that helps people identify potential harms from the AI applications they are prototyping. Based on a user's prompt, Farsight highlights news articles about relevant AI incidents and allows users to explore and edit LLM-generated use cases, stakeholders, and harms. We report design insights from a co-design study with 10 AI prototypers and findings from a user study with 42 AI prototypers. After using Farsight, AI prototypers in our user study are better able to independently identify potential harms associated with a prompt and find our tool more useful and usable than existing resources. Their qualitative feedback also highlights that Farsight encourages them to focus on end-users and think beyond immediate harms. We discuss these findings and reflect on their implications for designing AI prototyping experiences that meaningfully engage with AI harms. Farsight is publicly accessible at: https://PAIR-code.github.io/farsight., Comment: Accepted to CHI 2024. 40 pages, 19 figures, 5 tables. For a demo video, see https://youtu.be/BlSFbGkOlHk. For a live demo, visit https://PAIR-code.github.io/farsight. The source code is available at https://github.com/PAIR-code/farsight
- Published
- 2024
- Full Text
- View/download PDF
13. Practice development amidst a pandemic: a pilot programme to develop leadership in infection prevention and control professionals.
- Author
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Jain, S, Dempsey, K, Wilcox, S, Bradd, P, Travaglia, J, Debono, D, Justin, L, Hor, S-Y, Jain, S, Dempsey, K, Wilcox, S, Bradd, P, Travaglia, J, Debono, D, Justin, L, and Hor, S-Y
- Abstract
PURPOSE: This paper aims to describe the design and evaluation of a pilot leadership development programme for infection prevention and control (IPAC) professionals during the COVID-19 pandemic. The programme's aim was to improve IPAC knowledge and capacity in the health-care system by developing the leadership skills and capacities of novice and advanced Infection Control Professionals (ICPs), to respond flexibly, and competently, in their expanding and ever-changing roles. DESIGN/METHODOLOGY/APPROACH: The leadership programme was piloted with seven nurses, who were part of a clinical nursing team in New South Wales, Australia, over a 12-month period between 2021 and 2022. The programme was designed using a leadership development framework underpinned by transformational leadership theory, practice development approaches and collaborative and experiential learning. These principles were applied during programme design, with components adapted to learners' interests and regular opportunities provided for collaboration in active learning and critical reflection on workplace experiences. FINDINGS: The authors' evaluation suggests that the programme was feasible, acceptable and considered to be effective by this cohort. Moreover, participants valued the opportunities to engage in active and experience-based learning with peers, and with the support of senior and experienced ICPs. The action learning sets were well-received and allowed participants to critically reflect on and learn from one another's experiences. The mentoring programme allowed them to apply their developing leadership skills to real workplace challenges that they face. RESEARCH LIMITATIONS/IMPLICATIONS: Despite a small sample size, the authors' results provide empirical evidence about the effectiveness of using a practice development approach for strengthening ICP leadership capacity. The success of this pilot study has paved the way for a bigger second cohort of participants in the programme, for whi
- Published
- 2024
14. Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
- Author
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Fiedler, S., Naik, V., O'Connor, F.M., Smith, C.J., Griffiths, P., Kramer, R.J., Takemura, T., Allen, R.J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D.., Westervelt, D.M., Wilcox, L.J., Zhao, A., Collins, W.J., Schulz, M., Myhre, G., Forster, P.M., Fiedler, S., Naik, V., O'Connor, F.M., Smith, C.J., Griffiths, P., Kramer, R.J., Takemura, T., Allen, R.J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D.., Westervelt, D.M., Wilcox, L.J., Zhao, A., Collins, W.J., Schulz, M., Myhre, G., and Forster, P.M.
- Abstract
he climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the unde
- Published
- 2024
- Full Text
- View/download PDF
15. Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
- Author
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Fiedler, S., Naik, V., O'Connor, F.M., Smith, C.J., Griffiths, P., Kramer, R.J., Takemura, T., Allen, R.J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D.., Westervelt, D.M., Wilcox, L.J., Zhao, A., Collins, W.J., Schulz, M., Myhre, G., Forster, P.M., Fiedler, S., Naik, V., O'Connor, F.M., Smith, C.J., Griffiths, P., Kramer, R.J., Takemura, T., Allen, R.J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D.., Westervelt, D.M., Wilcox, L.J., Zhao, A., Collins, W.J., Schulz, M., Myhre, G., and Forster, P.M.
- Abstract
he climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the unde
- Published
- 2024
- Full Text
- View/download PDF
16. Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
- Author
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Fiedler, S., Naik, V., O'Connor, F.M., Smith, C.J., Griffiths, P., Kramer, R.J., Takemura, T., Allen, R.J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D.., Westervelt, D.M., Wilcox, L.J., Zhao, A., Collins, W.J., Schulz, M., Myhre, G., Forster, P.M., Fiedler, S., Naik, V., O'Connor, F.M., Smith, C.J., Griffiths, P., Kramer, R.J., Takemura, T., Allen, R.J., Im, U., Kasoar, M., Modak, A., Turnock, S., Voulgarakis, A., Watson-Parris, D.., Westervelt, D.M., Wilcox, L.J., Zhao, A., Collins, W.J., Schulz, M., Myhre, G., and Forster, P.M.
- Abstract
he climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood, and uncertainty in climate model results persists, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. We synthesize current challenges and emphasize opportunities for advancing our understanding of the interactions between atmospheric composition, air quality, and climate change, as well as for quantifying model diversity. Our perspective is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specializations across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation–response paradigm through multi-model ensembles of Earth system models of varying complexity. We discuss the challenges of gaining insights from Earth system models that face computational and process representation limits and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible and machine learning approaches where they are needed, e.g., for faster and better subgrid-scale parameterizations and pattern recognition in big data. New model constraints can arise from augmented observational products that leverage multiple datasets with machine learning approaches. Future MIPs can develop smart experiment protocols that strive towards an optimal trade-off between the resolution, complexity, and number of simulations and their length and, thereby, help to advance the unde
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- 2024
- Full Text
- View/download PDF
17. A community palm model
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Clinton, Nicholas, Vollrath, Andreas, D'annunzio, Remi, Liu, Desheng, Glick, Henry B., Descals, Adrià, Sullivan, Alicia, Guinan, Oliver, Abramowitz, Jacob, Stolle, Fred, Goodman, Chris, Birch, Tanya, Quinn, David, Danylo, Olga, Lips, Tijs, Coelho, Daniel, Bihari, Enikoe, Cronkite-Ratcliff, Bryce, Poortinga, Ate, Haghighattalab, Atena, Notman, Evan, DeWitt, Michael, Yonas, Aaron, Donchyts, Gennadii, Shah, Devaja, Saah, David, Tenneson, Karis, Quyen, Nguyen Hanh, Verma, Megha, Wilcox, Andrew, Clinton, Nicholas, Vollrath, Andreas, D'annunzio, Remi, Liu, Desheng, Glick, Henry B., Descals, Adrià, Sullivan, Alicia, Guinan, Oliver, Abramowitz, Jacob, Stolle, Fred, Goodman, Chris, Birch, Tanya, Quinn, David, Danylo, Olga, Lips, Tijs, Coelho, Daniel, Bihari, Enikoe, Cronkite-Ratcliff, Bryce, Poortinga, Ate, Haghighattalab, Atena, Notman, Evan, DeWitt, Michael, Yonas, Aaron, Donchyts, Gennadii, Shah, Devaja, Saah, David, Tenneson, Karis, Quyen, Nguyen Hanh, Verma, Megha, and Wilcox, Andrew
- Abstract
Palm oil production has been identified as one of the major drivers of deforestation for tropical countries. To meet supply chain objectives, commodity producers and other stakeholders need timely information of land cover dynamics in their supply shed. However, such data are difficult to obtain from suppliers who may lack digital geographic representations of their supply sheds and production locations. Here we present a "community model," a machine learning model trained on pooled data sourced from many different stakeholders, to develop a specific land cover probability map, in this case a semi-global oil palm map. An advantage of this method is the inclusion of varied inputs, the ability to easily update the model as new training data becomes available and run the model on any year that input imagery is available. Inclusion of diverse data sources into one probability map can help establish a shared understanding across stakeholders on the presence and absence of a land cover or commodity (in this case oil palm). The model predictors are annual composites built from publicly available satellite imagery provided by Sentinel-1, Sentinel-2, and ALOS DSM. We provide map outputs as the probability of palm in a given pixel, to reflect the uncertainty of the underlying state (palm or not palm). The initial version of this model provides global accuracy estimated to be approximately 90% (at 0.5 probability threshold) from spatially partitioned test data. This model, and resulting oil palm probability map products are useful for accurately identifying the geographic footprint of palm cultivation. Used in conjunction with timely deforestation information, this palm model is useful for understanding the risk of continued oil palm plantation expansion in sensitive forest areas., Comment: v0
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- 2024
18. Elements of World Knowledge (EWOK): A cognition-inspired framework for evaluating basic world knowledge in language models
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Ivanova, Anna A., Sathe, Aalok, Lipkin, Benjamin, Kumar, Unnathi, Radkani, Setayesh, Clark, Thomas H., Kauf, Carina, Hu, Jennifer, Pramod, R. T., Grand, Gabriel, Paulun, Vivian, Ryskina, Maria, Akyürek, Ekin, Wilcox, Ethan, Rashid, Nafisa, Choshen, Leshem, Levy, Roger, Fedorenko, Evelina, Tenenbaum, Joshua, Andreas, Jacob, Ivanova, Anna A., Sathe, Aalok, Lipkin, Benjamin, Kumar, Unnathi, Radkani, Setayesh, Clark, Thomas H., Kauf, Carina, Hu, Jennifer, Pramod, R. T., Grand, Gabriel, Paulun, Vivian, Ryskina, Maria, Akyürek, Ekin, Wilcox, Ethan, Rashid, Nafisa, Choshen, Leshem, Levy, Roger, Fedorenko, Evelina, Tenenbaum, Joshua, and Andreas, Jacob
- Abstract
The ability to build and leverage world models is essential for a general-purpose AI agent. Testing such capabilities is hard, in part because the building blocks of world models are ill-defined. We present Elements of World Knowledge (EWOK), a framework for evaluating world modeling in language models by testing their ability to use knowledge of a concept to match a target text with a plausible/implausible context. EWOK targets specific concepts from multiple knowledge domains known to be vital for world modeling in humans. Domains range from social interactions (help/hinder) to spatial relations (left/right). Both, contexts and targets are minimal pairs. Objects, agents, and locations in the items can be flexibly filled in enabling easy generation of multiple controlled datasets. We then introduce EWOK-CORE-1.0, a dataset of 4,374 items covering 11 world knowledge domains. We evaluate 20 openweights large language models (1.3B--70B parameters) across a battery of evaluation paradigms along with a human norming study comprising 12,480 measurements. The overall performance of all tested models is worse than human performance, with results varying drastically across domains. These data highlight simple cases where even large models fail and present rich avenues for targeted research on LLM world modeling capabilities., Comment: 21 pages (11 main), 7 figures. Authors Anna Ivanova, Aalok Sathe, Benjamin Lipkin contributed equally
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- 2024
19. An Energy Stable High-Order Cut Cell Discontinuous Galerkin Method with State Redistribution for Wave Propagation
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Taylor, Christina G., Wilcox, Lucas C., Chan, Jesse, Taylor, Christina G., Wilcox, Lucas C., and Chan, Jesse
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Cut meshes are a type of mesh that is formed by allowing embedded boundaries to "cut" a simple underlying mesh resulting in a hybrid mesh of cut and standard elements. While cut meshes can allow complex boundaries to be represented well regardless of the mesh resolution, their arbitrarily shaped and sized cut elements can present issues such as the small cell problem, where small cut elements can result in a severely restricted CFL condition. State redistribution, a technique developed by Berger and Giuliani [1], can be used to address the small cell problem. In this work, we pair state redistribution with a high-order discontinuous Galerkin scheme that is $L_2$ energy stable for arbitrary quadrature. We prove that state redistribution can be added to a provably $L_2$ energy stable discontinuous Galerkin method on a cut mesh without damaging the scheme's $L_2$ stability. We numerically verify the high order accuracy and stability of our scheme on two-dimensional wave propagation problems.
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- 2024
20. [Call for Papers] The 2nd BabyLM Challenge: Sample-efficient pretraining on a developmentally plausible corpus
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Choshen, Leshem, Cotterell, Ryan, Hu, Michael Y., Linzen, Tal, Mueller, Aaron, Ross, Candace, Warstadt, Alex, Wilcox, Ethan, Williams, Adina, Zhuang, Chengxu, Choshen, Leshem, Cotterell, Ryan, Hu, Michael Y., Linzen, Tal, Mueller, Aaron, Ross, Candace, Warstadt, Alex, Wilcox, Ethan, Williams, Adina, and Zhuang, Chengxu
- Abstract
After last year's successful BabyLM Challenge, the competition will be hosted again in 2024/2025. The overarching goals of the challenge remain the same; however, some of the competition rules will be different. The big changes for this year's competition are as follows: First, we replace the loose track with a paper track, which allows (for example) non-model-based submissions, novel cognitively-inspired benchmarks, or analysis techniques. Second, we are relaxing the rules around pretraining data, and will now allow participants to construct their own datasets provided they stay within the 100M-word or 10M-word budget. Third, we introduce a multimodal vision-and-language track, and will release a corpus of 50% text-only and 50% image-text multimodal data as a starting point for LM model training. The purpose of this CfP is to provide rules for this year's challenge, explain these rule changes and their rationale in greater detail, give a timeline of this year's competition, and provide answers to frequently asked questions from last year's challenge.
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- 2024
21. Responses of Harmful Algal Bloom-Causing Phytoplankton Taxa to Atmospheric Rivers Along the California Coast
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Wilcox, Jeri, Wilcox, Jeri, Wilcox, Jeri, and Wilcox, Jeri
- Abstract
It is important to understand the complex physical and biological interactions of the climate system for the adaptation to and mitigation of the many consequences of climate change. This study aimed to understand the impacts of Atmospheric Rivers (ARs) on Harmful Algal Bloom (HAB) causing phytoplankton taxa. ARs are ephemeral corridors of the atmosphere carrying massive amounts of water vapor from the tropics to mid latitudes and are strongly correlated with orographic precipitation. ARs are defined and characterized by the vertically Integrated Vapor Transport (IVT), which is the measured amount of water and its movement in the atmospheric column. Abundances of 13 different taxa of phytoplankton associated with HABs at 12 different monitoring stations along the California Coast were obtained from CalHABMAP. IVT magnitudes as well as a chronology of AR occurrences at 0.25° by 0.25° grid cells at each of these 12 locations were obtained from the CW3E, which acquired the information from ECMWF ERA5 Reanalysis data. Here I attempt to answer two questions: 1) When a specific HAB-causing phytoplankton taxon was present, was its abundance correlated with the IVT magnitude the week prior to sampling? 2) When this HAB-causing phytoplankton taxon was present, was its abundance different when an AR occurred during the week prior to sampling versus no AR? To reveal potential relationships between phytoplankton abundance with the IVT magnitude or presence of ARs, I quantified correlations between the phytoplankton abundances and the IVT magnitude or AR occurrence the week before phytoplankton sampling. Some dinoflagellate taxa showed consistent positive correlations in Northern California, while different dinoflagellate taxa showed more consistent negative correlations in Southern California. AR presence consistently was associated with a decrease in the abundance of phytoplankton in most diatom and dinoflagellate taxa. With little latitudinal trend in the sign of the correlati
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- 2023
22. Structural Studies of Adenosine Deaminases Acting on RNA for the Development and Optimization of Therapeutic Site-Directed RNA and DNA Editing
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Wilcox, Xander, Fisher, Andrew J1, Wilcox, Xander, Wilcox, Xander, Fisher, Andrew J1, and Wilcox, Xander
- Abstract
Adenosine-to-inosine RNA editing catalyzed by the family of enzymes Adenosine Deaminases Acting on RNA (ADARs) plays several important roles in biological homeostasis of metazoans. Hydrolytic deamination of adenosine by ADARs results in the formation of inosine, which is read by cellular machinery as guanosine. This A-to-G information change can impact miRNA/siRNA biogenesis, splicing, mRNA recoding, and the innate immune response. Humans encode three ADAR genes, with ADAR1 and ADAR2 being catalytically active enzymes with distinct substrate preferences. Structural biology has been shown to be an important tool for understanding the basic mechanism and substrate specificity of ADARs. Information gleaned from structural studies can be used to optimize therapeutic site-directed RNA editing platforms, develop new genome editing technologies, and design ADAR inhibitor drugs for the treatment of cancer. Chapter 1 of this dissertation begins with an overview of the various modifications that occur in RNA, with an emphasis on adenosine-to-inosine RNA editing by ADARs. Next, I discuss the mechanism and substrate specificity of ADARs, the diverse biological implications of ADAR editing, and how aberrant editing is implicated in several human diseases. I go on to discuss how ADARs have been used to develop therapeutic site-directed RNA editing technologies. Lastly, I finish with a discussion of the structural information of ADARs to date and how these structures have provided important mechanistic and substrate specificity information. Chapters 2 and 3 describe highly collaborative studies to optimize guide oligonucleotide design for the site-directed RNA editing with endogenous ADARs. Chapter 2 examines modified nucleotides at the orphan base position to enhance on-target editing by endogenous ADARs. Benner’s base dZ was shown to enhance ADAR base-flipping, catalysis, and on-target editing by wild type ADAR. A high-resolution crystal structure of the deaminase domain of ADAR
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- 2023
23. A second update on mapping the human genetic architecture of COVID-19
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Kanai, M, Andrews, S, Cordioli, M, Stevens, C, Neale, B, Daly, M, Ganna, A, Pathak, G, Iwasaki, A, Karjalainen, J, Mehtonen, J, Pirinen, M, Chwialkowska, K, Trankiem, A, Balaconis, M, Veerapen, K, Wolford, B, Ahmad, H, von Hohenstaufen Puoti, K, Boer, C, Boua, P, Butler-Laporte, G, Cadilla, C, Chwiałkowska, K, Colombo, F, Douillard, V, Dueker, N, Dutta, A, El-Sherbiny, Y, Eltoukhy, M, Esmaeeli, S, Faucon, A, Fave, M, Cadenas, I, Francescatto, M, Francioli, L, Franke, L, Fuentes, M, Durán, R, Cabrero, D, Harry, E, Jansen, P, Szentpéteri, J, Kaja, E, Kirk, C, Kousathanas, A, Krieger, J, Patel, S, Lemaçon, A, Limou, S, Lió, P, Marouli, E, Marttila, M, Medina-Gómez, C, Michaeli, Y, Migeotte, I, Mondal, S, Moreno-Estrada, A, Moya, L, Nakanishi, T, Nasir, J, Pasko, D, Pearson, N, Pereira, A, Priest, J, Prijatelj, V, Prokić, I, Teumer, A, Várnai, R, Romero-Gómez, M, Roos, C, Rosenfeld, J, Ruolin, L, Schulte, E, Schurmann, C, Sedaghati-khayat, B, Shaheen, D, Shivanathan, I, Sipeky, C, Sirui, Z, Striano, P, Tanigawa, Y, Remesal, A, Vadgama, N, Vallerga, C, van der Laan, S, Verdugo, R, Wang, Q, Wei, Z, Zainulabid, U, Zárate, R, Auton, A, Shelton, J, Shastri, A, Weldon, C, Filshtein-Sonmez, T, Coker, D, Symons, A, Aslibekyan, S, O’Connell, J, Ye, C, Hatoum, A, Agrawal, A, Bogdan, R, Colbert, S, Thompson, W, Fan, C, Johnson, E, Niazyan, L, Davidyants, M, Arakelyan, A, Avetyan, D, Bekbossynova, M, Tauekelova, A, Tuleutayev, M, Sailybayeva, A, Ramankulov, Y, Zholdybayeva, E, Dzharmukhanov, J, Kassymbek, K, Tsechoeva, T, Turebayeva, G, Smagulova, Z, Muratov, T, Khamitov, S, Kwong, A, Timpson, N, Niemi, M, Rahmouni, S, Guntz, J, Beguin, Y, Pigazzini, S, Nkambule, L, Georges, M, Moutschen, M, Misset, B, Darcis, G, Gofflot, S, Bouysran, Y, Busson, A, Peyrassol, X, Wilkin, F, Pichon, B, Smits, G, Vandernoot, I, Goffard, J, Tiembe, N, Morrison, D, Afilalo, J, Mooser, V, Richards, J, Rousseau, S, Durand, M, Forgetta, V, Laurent, L, Afrasiabi, Z, Bouab, M, Tselios, C, Xue, X, Afilalo, M, Oliveira, M, St-Cyr, J, Boisclair, A, Ragoussis, J, Auld, D, Kaufmann, D, Lathrop, G, Bourque, G, Décary, S, Falcone, E, Montpetit, A, Piché, A, Renoux, C, Tremblay, K, Tse, S, Zawati, M, Davis, L, Cox, N, Below, J, Sealock, J, Shuey, M, Polikowsky, H, Petty, L, Shaw, D, Chen, H, Zhu, W, Schmidt, A, Ludwig, K, Maj, C, Rolker, S, Balla, D, Behzad, P, Nöthen, M, Fazaal, J, Keitel, V, Jensen, B, Feldt, T, Marx, N, Dreher, M, Pink, I, Cornberg, M, Illig, T, Lehmann, C, Schommers, P, Rybniker, J, Augustin, M, Knopp, L, Kurth, I, Eggermann, T, Volland, S, Berger, M, Brenner, T, Hinney, A, Witzke, O, Konik, M, Bals, R, Herr, C, Ludwig, N, Walter, J, Latz, E, Schmidt, S, Brooks, J, Bull, S, Elliott, L, Gagnon, F, Greenwood, C, Hung, R, Lawless, J, Paterson, A, Sun, L, Rauh, M, Briollais, L, Gingras, A, Bombard, Y, Pugh, T, Simpson, J, Goneau, L, Halevy, A, Maslove, D, Borgundvaag, B, Devine, L, Bearss, E, Richardson, D, Arnoldo, S, Friedman, S, Taher, A, Stern, S, Dagher, M, Vasilevska-Ristovska, J, Biggs, C, Mickiewicz, B, Strug, L, Scherer, S, Aziz, N, Jones, S, Knoppers, B, Lathrop, M, Turvey, S, Yeung, R, Allen, U, Cheung, A, Herridge, M, Hunt, M, Lerner-Ellis, J, Taher, J, Parekh, R, Hiraki, L, Cowan, J, Ducharme, F, Ostrowski, M, Bernier, F, Kellner, J, Garg, E, Yoo, S, Vlasschaert, C, Frangione, E, Chung, M, Noor, A, Greenfeld, E, Colwill, K, Clausen, M, Chao, G, Yue, F, Fritzler, M, Whitney, J, Thiruvahindrapuram, B, Garant, J, Abraham, R, Davis, A, Campigotto, A, Papenburg, J, Niranjan, K, Betschel, S, Sadarangani, M, Barton-Forbes, M, Hanley, M, Fung, C, Lapadula, E, Macdonald, G, Puopolo, M, Kaushik, D, Nirmalanathan, K, Wong, I, Khan, Z, Zarei, N, Michalowska, M, Modi, B, Persia, P, Estacio, A, Buchholz, M, Cheatley, P, Lorenti, M, Aman, N, Matveev, V, Budylowski, P, Upton, J, Morris, S, Boyd, T, Chowdhary, S, Casalino, S, Morgan, G, Mighton, C, Mcgeer, A, Mazzulli, T, Mcleod, S, Binnie, A, Faghfoury, H, Chertkow, H, Racher, H, Serbanescu, M, Pavenski, K, Esser, M, Thompson, G, Herbrick, J, Gignoux, C, Wicks, S, Crooks, K, Barnes, K, Daya, M, Shortt, J, Rafaels, N, Chavan, S, Schulze, T, Heilbronner, U, Papiol, S, Corbetta, A, Wendtner, C, Spinner, C, Erber, J, Schneider, J, Winter, C, Wiltfang, J, Budde, M, Senner, F, Kalman, J, Protzer, U, Mueller, N, Mousas, A, Liontos, A, Christaki, E, Milionis, H, Tsilidis, K, Asimakopoulos, A, Kanellopoulou, A, Markozannes, G, Biros, D, Milionis, O, Tsourlos, S, Athanasiou, L, Kolios, N, Pappa, C, Papathanasiou, A, Pargana, E, Nasiou, M, Kosmidou, M, Rapti, I, Ntotsikas, E, Chaliasos, K, Ntzani, E, Evangelou, E, Gartzonika, K, Georgiou, I, Tzoulaki, I, Ellinghaus, D, Degenhardt, F, Cáceres, M, Juzenas, S, Lenz, T, Albillos, A, Julià, A, Prati, D, Solligård, E, Garcia, F, Tran, F, Hanses, F, Baselli, G, Zoller, H, Holter, J, Fernández, J, Barretina, J, Valenti, L, Bujanda, L, Buti, M, D’Amato, M, Banales, J, Rosenstiel, P, Koehler, P, Invernizzi, P, de Cid, R, Asselta, R, Schreiber, S, Duga, S, Hehr, U, Franke, A, Maya-Miles, D, Hov, J, Karlsen, T, Folseraas, T, Teles, A, Tanck, A, Gassner, C, Azuure, C, Wacker, E, Uellendahl-Werth, F, Hemmrich-Stanisak, G, Elabd, H, Kässens, J, Arora, J, Lerga-Jaso, J, Wienbrandt, L, Rühlemann, M, Wendorff, M, Figuera Basso, M, Vadla, M, Wittig, M, Braun, N, Lenning, O, Özer, O, Myhre, R, Raychaudhuri, S, Wesse, T, Albrecht, W, Yi, X, Ortiz, A, de Salazar, A, Chercoles, A, Palom, A, Ruiz, A, Garcia-Fernandez, A, Blanco-Grau, A, Mantovani, A, Holten, A, Bandera, A, Cherubini, A, Protti, A, Aghemo, A, Gerussi, A, Ramirez, A, Nebel, A, Barreira, A, Lleo, A, Kildal, A, Biondi, A, Caballero-Garralda, A, Gori, A, Glück, A, Lind, A, Nolla, A, Latiano, A, Fracanzani, A, Peschuck, A, Cavallero, A, Dyrhol-Riise, A, Ruello, A, Muscatello, A, Voza, A, Rando-Segura, A, Solier, A, Cortes, B, Mateos, B, Nafria-Jimenez, B, Schaefer, B, Bellinghausen, C, Ferrando, C, de la Horra, C, Quereda, C, Scollo, C, Lange, C, Hu, C, Paccapelo, C, Angelini, C, Cappadona, C, Bianco, C, Cea, C, Sancho, C, Hoff, D, Galimberti, D, Haschka, D, Jiménez, D, Pestaña, D, Toapanta, D, Muñiz-Diaz, E, Azzolini, E, Sandoval, E, Binatti, E, Scarpini, E, Casalone, E, Urrechaga, E, Paraboschi, E, Pontali, E, Reverter, E, Calderón, E, Navas, E, Contro, E, Arana-Arri, E, Aziz, F, Sánchez, F, Ceriotti, F, Martinelli-Boneschi, F, Peyvandi, F, Blasi, F, Malvestiti, F, Medrano, F, Mesonero, F, Rodriguez-Frias, F, Müller, F, Bellani, G, Pesenti, A, Zanella, A, Grasselli, G, Pezzoli, G, Costantino, G, Albano, G, Cardamone, G, Bellelli, G, Citerio, G, Foti, G, Lamorte, G, Matullo, G, Kurihara, H, Neb, H, My, I, Hernández, I, de Rojas, I, Galván-Femenia, I, Afset, J, Heyckendorf, J, Damås, J, Ampuero, J, Martín, J, Erdmann, J, Badia, J, Dopazo, J, Bergan, J, Quero, J, Goikoetxea, J, Delgado, J, Guerrero, J, Risnes, K, Banasik, K, Müller, K, Gaede, K, Garcia-Etxebarria, K, Tonby, K, Heggelund, L, Bettini, L, Sumoy, L, Terranova, L, Gustad, L, Garbarino, L, Santoro, L, Téllez, L, Roade, L, Ostadreza, M, Intxausti, M, Kogevinas, M, Riveiro-Barciela, M, Schaefer, M, Gutiérrez-Stampa, M, Carrabba, M, Valsecchi, M, Hernandez-Tejero, M, Vehreschild, M, Manunta, M, Acosta-Herrera, M, D’Angiò, M, Baldini, M, Cazzaniga, M, Marquié, M, Castoldi, M, Cecconi, M, Tomasi, M, Boada, M, Joannidis, M, Mazzocco, M, Ciccarelli, M, Rodríguez-Gandía, M, Bocciolone, M, Miozzo, M, Ayo, N, Blay, N, Chueca, N, Montano, N, Martínez, N, Cornely, O, Palmieri, O, Faverio, P, Preatoni, P, Bonfanti, P, Omodei, P, Tentorio, P, Castro, P, Rodrigues, P, Izquierdo-Sanchez, L, España, P, Hoffmann, P, Bacher, P, de Pablo, R, Ferrer, R, Gualtierotti, R, Gallego-Durán, R, Nieto, R, Carpani, R, Morilla, R, Badalamenti, S, Haider, S, Ciesek, S, Bombace, S, Marsal, S, Klein, S, Pelusi, S, Wilfling, S, Goerg, S, Bosari, S, Brunak, S, Heilmann-Heimbach, S, Aliberti, S, Dudman, S, Zheng, T, Bahmer, T, Pumarola, T, Cejudo, T, Rimoldi, V, Monzani, V, Skogen, V, Friaza, V, Andrade, V, Moreno, V, Peter, W, Farre, X, Khodamoradi, Y, Grimsrud, M, May, S, Colombo, A, Virginia, M, Dorador, C, Fuentes-Guajardo, M, Silva, A, Espinosa-Parrilla, Y, Yáñez, C, Retamales-Ortega, R, Saez Hidalgo, J, Tobar-Calfucoy, E, Carvajal-Silva, L, Martínez, M, Cerpa, L, Christian, M, Cappelli, C, Valenzuela-Jorquera, H, Zapata-Contreras, D, Zuñiga-Pacheco, P, Nova-Lamperti, E, Sanhueza, S, Donoso, G, Bocchieri, P, Kochifas, P, Quiñones, L, Pedersen, O, Geller, F, Westergaard, D, Sequeros, C, Nissen, J, Nielsen, S, Feldt-Rasmussen, U, Bliddal, S, Grønbæk, K, Ullum, H, Ostrowski, S, Feenstra, B, Shahin, D, Sobh, A, Shoma, A, Nkambul, L, Elhadidy, T, Abd Elghafar, M, El-Jawhari, J, Mohamed, A, Elnagdy, M, Samir, A, Abdel-Aziz, M, Khafaga, W, El-Lawaty, W, Torky, M, El-Shanshory, M, Elzeiny, A, Rashad, A, Mansour, T, Yassen, A, Hegazy, M, Okasha, K, Eid, M, Hanteera, M, Medina-Gomez, C, Ikram, M, Uitterlinden, A, Ripatti, S, Jermy, B, Ruotsalainen, S, Kristiansson, K, Koskelainen, S, Perola, M, Donner, 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Margherita, Francioli, Laurent, Franke, Lude, Fuentes, Macarena, Durán, Rocío Gallego, Cabrero, David Gómez, Harry, Emi N., Jansen, Philip, Szentpéteri, József L., Kaja, Elżbieta, Kirk, Chloe, Kousathanas, Athanasios, Krieger, Jose E., Patel, Sanjay K., Lemaçon, Audrey, Limou, Sophie, Lió, Pietro, Marouli, Eirini, Marttila, Minttu M., Medina-Gómez, Carolina, Michaeli, Yael, Migeotte, Isabelle, Mondal, Soumyajit, Moreno-Estrada, Andrés, Moya, Leire, Nakanishi, Tomoko, Nasir, Jamal, Pasko, Dorote, Pearson, Nathaniel M., Pereira, Alexandre C., Priest, James, Prijatelj, Vid, Prokić, Ivana, Teumer, Alexander, Várnai, Réka, Romero-Gómez, Manuel, Roos, Christina, Rosenfeld, Jeffrey, Ruolin, Li, Schulte, Eva C., Schurmann, Claudia, Sedaghati-khayat, Bahar, Shaheen, Doaa, Shivanathan, Ilangumaran, Sipeky, Csilla, Sirui, Zhou, Striano, Pasquale, Tanigawa, Yosuke, Remesal, Alicia Utrilla, Vadgama, Nirmal, Vallerga, Costanza L., van der Laan, Sander, Verdugo, Ricardo A., Wang, Qingbo S., Wei, Zhou, Zainulabid, Ummu Afeera, Zárate, Ruth N., Auton, Adam, Shelton, Janie F., Shastri, Anjali J., Weldon, Catherine H., Filshtein-Sonmez, Teresa, Coker, Daniella, Symons, Antony, Aslibekyan, Stella, O’Connell, Jared, Ye, Chelsea, Hatoum, Alexander S., Agrawal, Arpana, Bogdan, Ryan, Colbert, Sarah M. C., Thompson, Wesley K., Fan, Chun Chieh, Johnson, Emma C., Niazyan, Lyudmila, Davidyants, Mher, Arakelyan, Arsen, Avetyan, Diana, Bekbossynova, Makhabbat, Tauekelova, Ainur, Tuleutayev, Mukhtar, Sailybayeva, Aliya, Ramankulov, Yerlan, Zholdybayeva, Elena, Dzharmukhanov, Jarkyn, Kassymbek, Kuat, Tsechoeva, Tatyana, Turebayeva, Gulsimzhan, Smagulova, Zauresh, Muratov, Timur, Khamitov, Sadyk, Kwong, Alex S. F., Timpson, Nicholas J., Niemi, Mari E. K., Rahmouni, Souad, Guntz, Julien, Beguin, Yves, Pigazzini, Sara, Nkambule, Lindokuhle, Georges, Michel, Moutschen, Michel, Misset, Benoit, Darcis, Gilles, Gofflot, Stéphanie, Bouysran, Youssef, Busson, Adeline, Peyrassol, Xavier, Wilkin, Françoise, Pichon, Bruno, Smits, Guillaume, Vandernoot, Isabelle, Goffard, Jean-Christophe, Tiembe, Nicky, Morrison, David R., Afilalo, Jonathan, Mooser, Vincent, Richards, J. Brent, Rousseau, Simon, Durand, Madeleine, Forgetta, Vincenzo, Laurent, Laetitia, Afrasiabi, Zaman, Bouab, Meriem, Tselios, Chris, Xue, Xiaoqing, Afilalo, Marc, Oliveira, Maureen, St-Cyr, Janick, Boisclair, Ariane, Ragoussis, Jiannis, Auld, Daniel, Kaufmann, Daniel E., Lathrop, G. Mark, Bourque, Guillaume, Décary, Simon, Falcone, Emilia Liana, Montpetit, Alexandre, Piché, Alain, Renoux, Christel, Tremblay, Karine, Tse, Sze Man, Zawati, Ma’n H., Davis, Lea K., Cox, Nancy J., Below, Jennifer E., Sealock, Julia M., Faucon, Annika B., Shuey, Megan M., Polikowsky, Hannah G., Petty, Lauren E., Shaw, Douglas M., Chen, Hung-Hsin, Zhu, Wanying, Schmidt, Axel, Ludwig, Kerstin U., Maj, Carlo, Rolker, Selina, Balla, Daniella, Behzad, Pari, Nöthen, Markus M., Fazaal, Julia, Keitel, Verena, Jensen, Björn-Erik Ole, Feldt, Torsten, Marx, Nikolaus, Dreher, Michael, Pink, Isabell, Cornberg, Markus, Illig, Thomas, Lehmann, Clara, Schommers, Philipp, Rybniker, Jan, Augustin, Max, Knopp, Lisa, Kurth, Ingo, Eggermann, Thomas, Volland, Sonja, Berger, Marc M., Brenner, Thorsten, Hinney, Anke, Witzke, Oliver, Konik, Margarethe J., Bals, Robert, Herr, Christian, Ludwig, Nicole, Walter, Jörn, Latz, Eicke, Schmidt, Susanne V., Brooks, Jennifer D., Bull, Shelley, Elliott, Lloyd T., Gagnon, France, Greenwood, Celia M. T., Hung, Rayjean J., Lawless, Jerry F., Paterson, Andrew D., Sun, Lei, Rauh, Michael, Briollais, Laurent, Gingras, Anne-Claude, Bombard, Yvonne, Pugh, Trevor J., Simpson, Jared, Goneau, Lee W., Halevy, Anat R., Maslove, David M., Borgundvaag, Bjug, Devine, Luke, Bearss, Erin, Richardson, David, Arnoldo, Saranya, Friedman, Steven Marc, Taher, Ahmed, Stern, Seth, Dagher, Marc, Vasilevska-Ristovska, Jovanka, Biggs, Catherine M., Mickiewicz, Beata, Strug, Lisa J., Scherer, Stephen W., Aziz, Naveed, Jones, Steven J. M., Knoppers, Bartha M., Lathrop, Mark, Turvey, Stuart E., Yeung, Rae S. M., Allen, Upton, Cheung, Angela M., Herridge, Margaret S., Hunt, Miranda, Lerner-Ellis, Jordan, Taher, Jennifer, Parekh, Rulan S., Hiraki, Linda T., Cowan, Juthaporn, Ducharme, Francine M., Ostrowski, Mario, Bernier, Francois P., Kellner, Jim, Garg, Elika, Yoo, Samantha, Vlasschaert, Caitlyn, Frangione, Erika, Chung, Monica, Noor, Abdul, Greenfeld, Elena, Colwill, Karen, Clausen, Marc, Chao, Gary, Yue, FengYun, Fritzler, Marvin, Whitney, Joseph, Thiruvahindrapuram, Bhooma, Garant, Jean-Michel, Abraham, Rohan, Davis, Adrienne, Campigotto, Aaron, Papenburg, Jesse, Niranjan, Kissoon, Betschel, Stephen, Sadarangani, Manish, Barton-Forbes, Michelle, Hanley, Michaela, Fung, Chun Yiu Jordan, Lapadula, Elisa, MacDonald, Georgia, Puopolo, Michael, Kaushik, Deepanjali, Nirmalanathan, Konika, Wong, Iris, Khan, Zeeshan, Zarei, Natasha, Michalowska, Maria, Modi, Bhavi P., Persia, Pourshahnazari, Estacio, Antonio, Buchholz, Megan, Cheatley, Patti Lou, Lorenti, Miranda, Aman, Nowrin F., Matveev, Vitaliy, Budylowski, Patrick, Upton, Julia, Morris, Shaun, Boyd, Tracy, Chowdhary, Sunakshi, Casalino, Selina, Morgan, Gregory, Mighton, Chloe, McGeer, Allison, Mazzulli, Tony, McLeod, Shelley L., Binnie, Alexandra, Faghfoury, Hanna, Chertkow, Howard, Racher, Hilary, Serbanescu, Mihaela A., Pavenski, Katerina, Esser, Michael, Thompson, Graham, Herbrick, Jo-Anne, Gignoux, Christopher R., Wicks, Stephen J., Crooks, Kristy, Barnes, Kathleen C., Daya, Michelle, Shortt, Jonathan, Rafaels, Nicholas, Chavan, Sameer, Schulze, Thomas G., Heilbronner, Urs, Papiol, Sergi, Corbetta, Andrea, Wendtner, Clemens M., Spinner, Christoph D., Erber, Johanna, Schneider, Jochen, Winter, Christof, Wiltfang, Jens, Budde, Monika, Senner, Fanny, Kalman, Janos L., Protzer, Ulrike, Mueller, Nikola S., Mousas, Abdou, Liontos, Angelos, Christaki, Eirini, Milionis, Haralampos, Tsilidis, Konstantinos, Asimakopoulos, Alexandros, Kanellopoulou, Afroditi, Markozannes, Georgios, Biros, Dimitrios, Milionis, Orestis, Tsourlos, Stavros, Athanasiou, Lazaros, Kolios, Nikolaos-Gavriil, Pappa, Christiana, Papathanasiou, Alexandros, Pargana, Eleni, Nasiou, Maria, Kosmidou, Maria, Rapti, Iro, Ntotsikas, Evangelos, Chaliasos, Konstantinos, Ntzani, Evangelia, Evangelou, Evangelos, Gartzonika, Konstantina, Georgiou, Ioannis, Tzoulaki, Ioanna, Ellinghaus, David, Degenhardt, Frauke, Cáceres, Mario, Juzenas, Simonas, Lenz, Tobias L., Albillos, Agustín, Julià, Antonio, Prati, Daniele, Solligård, Erik, Garcia, Federico, Tran, Florian, Hanses, Frank, Baselli, Guido, Zoller, Heinz, Holter, Jan Cato, Fernández, Javier, Barretina, Jordi, Valenti, Luca, Bujanda, Luis, Buti, Maria, D’Amato, Mauro, Banales, Jesus M., Rosenstiel, Philip, Koehler, Philipp, Invernizzi, Pietro, de Cid, Rafael, Asselta, Rosanna, Schreiber, Stefan, Duga, Stefano, Hehr, Ute, Franke, Andre, Maya-Miles, Douglas, Hov, Johannes R., Karlsen, Tom H., Folseraas, Trine, Teles, Ana, Tanck, Anja, Gassner, Christoph, Azuure, Clinton, Wacker, Eike Matthias, Uellendahl-Werth, Florian, Hemmrich-Stanisak, Georg, ElAbd, Hesham, Kässens, Jan, Arora, Jatin, Lerga-Jaso, Jon, Wienbrandt, Lars, Rühlemann, Malte Christoph, Wendorff, Mareike, Figuera Basso, Maria E., Vadla, May Sissel, Wittig, Michael, Braun, Nicole, Lenning, Ole Bernt, Özer, Onur, Myhre, Ronny, Raychaudhuri, Soumya, Wesse, Tanja, Albrecht, Wolfgang, Yi, Xiaoli, Ortiz, Aaron Blandino, de Salazar, Adolfo, Chercoles, Adolfo Garrido, Palom, Adriana, Ruiz, Agustín, Garcia-Fernandez, Alba-Estela, Blanco-Grau, Albert, Mantovani, Alberto, Holten, Aleksander Rygh, Bandera, Alessandra, Cherubini, Alessandro, Protti, Alessandro, Aghemo, Alessio, Gerussi, Alessio, Ramirez, Alfredo, Nebel, Almut, Barreira, Ana, Lleo, Ana, Kildal, Anders Benjamin, Biondi, Andrea, Caballero-Garralda, Andrea, Gori, Andrea, Glück, Andreas, Lind, Andreas, Nolla, Anna Carreras, Latiano, Anna, Fracanzani, Anna Ludovica, Peschuck, Anna, Cavallero, Annalisa, Dyrhol-Riise, Anne Ma, Ruello, Antonella, Muscatello, Antonio, Voza, Antonio, Rando-Segura, Ariadna, Solier, Aurora, Cortes, Beatriz, Mateos, Beatriz, Nafria-Jimenez, Beatriz, Schaefer, Benedikt, Bellinghausen, Carla, Ferrando, Carlos, de la Horra, Carmen, Quereda, Carmen, Scollo, Chiara, Lange, Christoph, Hu, Cinzia, Paccapelo, Cinzia, Angelini, Claudio, Cappadona, Claudio, Bianco, Cristiana, Cea, Cristina, Sancho, Cristina, Hoff, Dag Arne Lihaug, Galimberti, Daniela, Haschka, David, Jiménez, David, Pestaña, David, Toapanta, David, Muñiz-Diaz, Eduardo, Azzolini, Elena, Sandoval, Elena, Binatti, Eleonora, Scarpini, Elio, Casalone, Elisabetta, Urrechaga, Eloisa, Paraboschi, Elvezia Maria, Pontali, Emanuele, Reverter, Enric, Calderón, Enrique J., Navas, Enrique, Contro, Ernesto, Arana-Arri, Eunate, Aziz, Fátima, Sánchez, Félix García, Ceriotti, Ferruccio, Martinelli-Boneschi, Filippo, Peyvandi, Flora, Blasi, Francesco, Malvestiti, Francesco, Medrano, Francisco J., Mesonero, Francisco, Rodriguez-Frias, Francisco, Müller, Fredrik, 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Valsecchi, Maria G., Hernandez-Tejero, María, Vehreschild, Maria J. G. T., Manunta, Maria, Acosta-Herrera, Marialbert, D’Angiò, Mariella, Baldini, Marina, Cazzaniga, Marina, Marquié, Marta, Castoldi, Massimo, Cecconi, Maurizio, Tomasi, Melissa, Boada, Mercè, Joannidis, Michael, Mazzocco, Michela, Ciccarelli, Michele, Rodríguez-Gandía, Miguel, Bocciolone, Monica, Miozzo, Monica, Ayo, Natale Imaz, Blay, Natalia, Chueca, Natalia, Montano, Nicola, Martínez, Nilda, Cornely, Oliver A., Palmieri, Orazio, Faverio, Paola, Preatoni, Paoletta, Bonfanti, Paolo, Omodei, Paolo, Tentorio, Paolo, Castro, Pedro, Rodrigues, Pedro M., Izquierdo-Sanchez, Laura, España, Pedro Pablo, Hoffmann, Per, Bacher, Petra, de Pablo, Raúl, Ferrer, Ricard, Gualtierotti, Roberta, Gallego-Durán, Rocío, Nieto, Rosa, Carpani, Rossana, Morilla, Rubén, Badalamenti, Salvatore, Haider, Sammra, Ciesek, Sandra, Bombace, Sara, Marsal, Sara, Klein, Sebastian, Pelusi, Serena, Wilfling, Sibylle, Goerg, Siegfried, Bosari, Silvano, Brunak, Søren, Heilmann-Heimbach, Stefanie, Aliberti, Stefano, Dudman, Susanne, Zheng, Tenghao, Bahmer, Thomas, Pumarola, Tomas, Cejudo, Trinidad Gonzalez, Rimoldi, Valeria, Monzani, Valter, Skogen, Vegard, Friaza, Vicente, Andrade, Victor, Moreno, Victor, Peter, Wolfgang, Farre, Xavier, Khodamoradi, Yascha, Grimsrud, Marit M., May, Sandra, Colombo, Alicia, Virginia, Monardes-Ramírez A., Dorador, Cristina, Fuentes-Guajardo, Macarena, Silva, Andrea X., Espinosa-Parrilla, Yolanda, Yáñez, Cristian E., Retamales-Ortega, Rocío M., Saez Hidalgo, Juan M., Tobar-Calfucoy, Eduardo A., Carvajal-Silva, Laura, Martínez, Matías F., Cerpa, Leslie C., Christian, Muñoz A., Cappelli, Claudio, Valenzuela-Jorquera, Hector, Zapata-Contreras, Daniela, Zuñiga-Pacheco, Paula, Nova-Lamperti, Estefania A., Sanhueza, Sergio A., Donoso, Gerardo, Bocchieri, Pamela, Kochifas, Pia, Quiñones, Luis A., Pedersen, Ole Birger, Geller, Frank, Westergaard, David, Sequeros, Celia Burgos, Nissen, Janna, Nielsen, Susanne Dam, Feldt-Rasmussen, Ulla, Bliddal, Sofie, Grønbæk, Kirsten, Ullum, Henrik, Ostrowski, Sisse Rye, Feenstra, Bjarke, Shahin, Doaa, Sobh, Ali, Shoma, Ashraf, Nkambul, Lindokuhle, Elhadidy, Tamer A., Abd Elghafar, Mohamed S., El-Jawhari, Jehan J., Mohamed, Attia A. S., Elnagdy, Marwa H., Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T., El-Lawaty, Walaa M., Torky, Mohamed S., El-Shanshory, Mohamed R., Elzeiny, Ahmed, Rashad, Amal, Mansour, Tamer A., Yassen, Amr M., Hegazy, Mohamed A. F., Okasha, Kamal, Eid, Mohammed A., Hanteera, Moahmed S., Medina-Gomez, Carolina, Ikram, M. Arfan, Uitterlinden, Andre G., Ripatti, Samuli, Jermy, Bradley, Ruotsalainen, Sanni, Kristiansson, Kati, Koskelainen, Sami, Perola, Markus, Donner, Kati, Kivinen, Katja, Palotie, Aarno, Kaunisto, Mari, Julienne, Hanna, Aschard, Hugues, Deleuze, Jean-Francois, Debette, Stephanie, Tregouet, David-Alexandre, Abel, Laurent, Henches, Léo, Lefloch, Edith, Claire, Dandine-Roulland, Sakuntabhai, Anavaj, Bourgeron, Thomas, Olaso, Robert, Daian, Delphine Bacq, Pellegrin, Isabelle, Casanova, Jean-Laurent, Cobat, Aurélie, Jouanguy, Emmanuelle, Zhang, Qian, Ghosn, Jade, Mentré, France, Laouénan, Cédric, Tubiana, Sarah, Chirouze, Catherine, Quintana-Murci, Luis, Patin, Etienne, Duffy, Darragh, Boland, Anne, Carreras, Anna, Galván-Femenía, Iván, Farré, Xavier, Cortés, Beatriz, Mercader, Josep Maria, Guindo-Martinez, Marta, Torrents, David, Garcia-Aymerich, Judith, Castaño-Vinyals, Gemma, Dobaño, Carlota, van Heel, David A., Hunt, Karen A., Trembath, Richard C., Jacobs, Benjamin Meir, Huang, Qin Qin, Martin, Hilary C., Mason, Dan, Trivedi, Bhavi, Wright, John, Munisamy, Malathy, Finer, Sarah, Griffiths, Christopher J., McCarthy, Mark I., Rosenberger, Carrie, Lee, Jong Eun, Chang, Diana, Hammer, Christian, Hunkapiller, Julie, Mahajan, Anubha, Pendergrass, Rion, Sucheston-Campbell, Lara, Yaspan, Brian, Lee, Hyun Soo, Shin, Eunsoon, Jang, Hye Yoon, Kim, Sunmie, Kym, Sungmin, Kim, Yeon-Sook, Jeong, Hyeongseok, Kwon, Ki Tae, Kim, Shin-Woo, Kim, Jin Yong, Jang, Young Rock, Kim, Hyun ah, Lee, Ji yeon, Lee, Jeong Eun, Lee, Shinwon, Choe, Kang-Won, Kang, Yu Min, Jee, Sun Ha, Jung, Keum Ji, Park, Hyun-Young, Kim, Bong-Jo, Kim, Young Jin, Hwang, Mi Yeong, Yoon, Kyungheon, Pairo-Castineira, Erola, Rawlik, Konrad, Caulfield, Mark J., Baillie, J. Kenneth, Griffiths, Fiona, Bretherick, Andrew D., Stuckey, Alex, Odhams, Christopher A., Walker, Susan, Russell, Clark D., Malinauskas, Tomas, Wu, Yang, Shen, Xia, Elliott, Katherine S., Morrice, Kirstie, Keating, Sean, Wang, Bo, Rhodes, Daniel, Klaric, Lucija, Zechner, Marie, Parkinson, Nick, Fawkes, Angie, Murphy, Lee, Vitart, Veronique, Wilson, James F., Yang, Jian, Scott, Richard H., Moutsianas, Loukas, Law, Andy, Begg, Colin, Hendry, Sara Clohisey, Hinds, Charles, Horby, Peter, Knight, Julian, Ling, Lowell, Maslove, David, McAuley, Danny, Millar, Johnny, Montgomery, Hugh, Nichol, Alistair, Openshaw, Peter J. M., Ponting, Chris P., Rowan, Kathy, Semple, Malcolm G., Shankar-Hari, Manu, Summers, Charlotte, Walsh, Timothy, Pan, Jacqueline, Grau, Neus, Jones, Tim Owen, Lim, Rosario, Marotti, Martina, Whitton, Christopher, Bociek, Aneta, Campos, Sara, Arbane, Gill, Ostermann, Marlies, Cha, Mina, DAmato, Fabiola, Kosifidou, Eirini, Lorah, Shelley, Morera, Kyma, Brady, Laura, Hugill, Keith, Henning, Jeremy, Bonner, Stephen, Headlam, Evie, Jones, Jessica, List, Abigail, Morley, Joanne, Welford, Amy, Kamangu, Bobette, Ratnakumar, Anitha, Shoremekun, Abiola, Alldis, Zoe, Astin-Chamberlain, Raine, Bibi, Fatima, Biddle, Jack, Blow, Sarah, Bolton, Matthew, Borra, Catherine, Bowles, Ruth, Burton, Maudrian, Choudhury, Yasmin, Cox, Amber, Easthope, Amy, Ebano, Patrizia, Fotiadis, Stavros, Gurasashvili, Jana, Halls, Rosslyn, Hartridge, Pippa, Kallon, Delordson, Kassam, Jamila, Lancoma-Malcolm, Ivone, Matharu, Maninderpal, May, Peter, Mitchelmore, Oliver, Newman, Tabitha, Patel, Mital, Pheby, Jane, Pinzuti, Irene, Prime, Zoe, Prysyazhna, Oleksandra, Shiel, Julian, Taylor, Melanie, Tierney, Carey, Zongo, Olivier, Wood, Suzanne, Zak, Anne, Collier, David, Mundy, Manuela, Thompson, Christopher, Pritchard, Lisa, Gellamucho, Minnie, Cartlidge, David, Bandla, Nageswar, Bailey, Lucy, Davies, Michelle, Delaney, Jane, Scott, Leanne, Abdelrazik, Marwa, Alasdair, Frater, Carter, David, Elhassan, Munzir, Ganesan, Arunkumar, Jenkins, Samuel, Lamond, Zoe, Purohit, Dharam, Rohit, Kumar, Saleem, Malik, Wall, Alanna, Xavier, Kugan, Bakthavatsalam, Dhanalaksmi, Gehad, Kirolos, Gnanapragasam, Pakeerathan, Jain, Kapil, Jain, Swati, Malik, Abdul, Pappachan, Naveen, Moreno-Cuesta, Jeronimo, Haldeos, Anne, Vincent, Rachel, Oziegb, Maryjane, Cavazza, Anna, Cockrell, Maeve, Corcoran, Eleanor, Depante, Maria, Finney, Clare, Jerome, Ellen, Knighton, Abigail, Nayak, Monalisa, Pappa, Evita, Saha, Rohit, Saha, Sian, Dodd, Andrew, O’Reilly, Kevin, McPhail, Mark, Clarey, Emma, Noble, Harriet, Smith, John, Coghlan, Phoebe, Brett, Stephen, Gordon, Anthony, Templeton, Maie, Antcliffe, David, Banach, Dorota, Darnell, Sarah, Fernandez, Ziortza, Jepson, Eleanor, Mohammed, Amal, Rojo, Roceld, Arias, Sonia Sousa, Gurung, Anita Tamang, Wong, Jenny, Fernandez-Roman, Jaime, Hamilton, David O., Johnson, Emily, Johnston, Brian, Martinez, Maria Lopez, Mulla, Suleman, Waite, Alicia A. C., Williams, Karen, Waugh, Victoria, Welters, Ingeborg, Emblem, Jessica, Norris, Maria, Shaw, David, Bashyal, Archana, Beer, Sally, Hutton, Paula, McKechnie, Stuart, Davidson, Neil, Mathew, Soya, Readion, Grace, Ryu, Jung, Wilson, Jean, Agrawal, Shruti, Elston, Kay, Jones, Megan, Meaney, Eoghan, Polgarova, Petra, Elbehery, Muhammad, Daubney, Esther, Ng, Anthony, Marshall, Jocelyn, Pathan, Nazima, Stroud, Katerina, White, Deborah, Andrew, Angela, Ashraf, Saima, Clark, Amy, Dent, Martin, Langley, Margaret, Peters, Cecilia, Ryan, Lucy, Sampson, Julia, Wei, Shuying, Baddeley, Alice, Meredith, Megan, Morris, Lucy, Gibbons, Alexandra, McLoughlin, Lisa, Delgado, Carlos Castro, Clark, Victoria, Dawson, Deborah, Ding, Lijun, Durrant, Georgia, Ezeobu, Obiageri, Harrison, Abiola, Hurt, William James, Kanu, Rebecca, Kinch, Ashley, Leaver, Susannah, Lisboa, Ana, Mathew, Jisha, Patel, Kamal, Saluzzio, Romina Pepermans, Rawlins, John, Samakomva, Tinashe, Shah, Nirav, Sicat, Christine, Texeira, Joana, Queiroz, Joana Gomes De, Gloria, Edna Fernandes Da, Maccacari, Elena, Yun, Nikki, Manna, Soumendu, Farnell-Ward, Sarah, Maizcordoba, Maria, Thanasi, Maria, Ali, Hawakin Haji, Hastings, Janice, Grauslyte, Lina, Hussain, Musarat, Ruge, Bobby, King, Sam, Pogreban, Tatiana, Rosaroso, Lace, Smith, Helen, Phull, Mandeep-Kaur, Adams, Nikkita, Franke, George, George, Aparna, Salciute, Erika, Wong, Joanna, Dunne, Karen, Flower, Luke, Sharland, Emma, Sra, Sukhmani, Andrew, Gillian, Callaghan, Marie, Barclay, Lucy, Marshall, Lucy, Amamio, Maria, Birch, Sophie, Briton, Kate, Clark, Sarah, Doverman, Katerine, Hope, Dave, Mcculloch, Corrienne, Simpson, Scott, Singleton, Jo, Fernandez, Rita, Allen, Meryem, Baptista, David, Crowe, Rebecca, Fox, Jonathan, Khera, Jacyntha, Loveridge, Adam, McKenley, India, Morino, Eriko, Naranjo, Andres, O’Connor, Denise, Simms, Richard, Sollesta, Kathryn, Swain, Andrew, Venkatesh, Harish, Herdman-Grant, Rosie, Joseph, Anna, Nown, Angela, Rose, Steve, Pogson, David, Boxall, Helen, Brimfield, Lutece, Claridge, Helen, Daly, Zoe, George, Shenu, Gribbin, Andrew, Cheema, Yusuf, Cutler, Sean, Richards, Owen, Roynon-Reed, Anna, Cherian, Shiney, Heron, Anne Emma, Williams, Gemma, Szakmany, Tamas, Waters, Abby, Collins, Kim, Dunhill, Jill, Jones, Ffion, Morris, Rebecca, Ship, Lucy, Cardwell, Amy, Ali, Syamlan, Bhatterjee, Ravi, Bolton, Rachel, Chukkambotla, Srikanth, Coleman, Dabheoc, Dalziel, Jack, Dykes, Joseph, Fine, Christopher, Gay, Bethan, Goddard, Wendy, Goodchild, Drew, Harling, Rhiannan, Hijazi, Muhammad, Keith, Sarah, Khan, Meherunnisa, Matt, Roseanna, Ryan-Smith, Janet, Saad, Samuel, Springle, Philippa, Thomas, Jacqueline, Truman, Nick, Kazi, Aayesha, Smith, Matthew, Collier, Heather, Davison, Chloe, Duberley, Stephen, Hargreaves, Jeanette, Hartley, Janice, Patel, Tahera, Smith, Ellen, Kent, Alissa, Goodwin, Emma, Zaki, Ahmed, Tibke, Clare, Hopkins, Susan, Gerrard, Hywel, Jackson, Matthew, Bennett, Sara, Marsh, Liane, Mills, Rebecca, Bell, Jessica, Campbell, Helen, Dawson, Angela, Dodds, Steve, Duffy, Stacey, Gallagher, Lisa, McCafferty, Gemma, Short, Stacey, Smith, Tracy, Thomas, Kirsty, Walker, Claire, Reynolds, Jessica, Yates, Bryan, McKie, Hayley, Panteli, Maria, Thompson, Maria, Waddell, Gail, Beger, Sarah De, Abraheem, Azmerelda, Dunmore, Charlie, Girach, Rumanah, Jones, Rhianna, London, Emily, Nagra, Imrun, Nasir, Farah, Sainsbury, Hannah, Smedley, Clare, Brearey, Stephen, Burchett, Caroline, Cawley, Kathryn, Faulkner, Maria, Jeffrey, Helen, Bamford, Peter, Shaikh, Firdaus, Slack, Lauren, Davies, Angela, Brooke, Hollie, Suarez, Jose Cebrian, Charlesworth, Ruth, Hansson, Karen, Norris, John, Poole, Alice, Sandhu, Rajdeep, Smithson, Elizabeth, Thirumaran, Muthu, Wagstaff, Veronica, Buckley, Sarah, Sloan, Brendan, Rose, Alastair, Major, Amy, Metcalfe, Alexandra, Almaden-Boyle, Christine, Austin, Pauline, Chapman, Susan, Eros, Alexandre, Cabrelli, Louise, Cole, Stephen, Whyte, Clare, Casey, Matt, Bafitis, Vasileios, Tsinaslanidis, George, George, Cassandra, Khade, Reena, Black, Christopher, Ashok, Sundar Raj, Farley, Sean, Brinkworth, Elaine, Harford, Rachel, Murphy, Carl, Williams, Marie, Newey, Luke, Toghill, Hannah, Lewis, Sophie, Rees, Tabitha, Battle, Ceri, Baker, Mark, Travers, Jenny, Chesters, Karen, Baxter, Nicola, Arnott, Andrew, McCreath, Gordan, McParland, Christopher, Rooney, Laura, Sim, Malcolm, Henderson, Steven, Abel, Lynn, Dalton, Carol, Kennedy-Hay, Sophie, O’Donohoe, Lynn, O’Hare, Megan, Orlikowska, Izabela, Parker, Natasha, McNeela, Fiona, Lyle, Amanda, Hughes, Alistair, Radhakrishnan, Jayachandran, Gibson, Sian, Bancroft, Hollie, Bellamy, Mary, Daglish, Jacqueline, Kadiri, Salma, Moore, Faye, Rhodes, Joanne, Sangombe, Mirriam, Peterkin, Zhane, Scriven, James, Carmody, Margaret, Cottle, Juliet, Peasgood, Emily, de Gordoa, Laura Ortiz-Ruiz, Phillips, Claire, Skinner, Denise, Cinquina, Zoe, Howard, Kate, Joy, Rosie, Roche, Samantha, Birkinshaw, Isobel, Carter, Joseph, Ingham, Jo, Marshall, Nicola, Pearson, Harriet, Scott, Zoe, Dasgin, Jo, Gill, Jaspret, Nilsson, Annette, Bamford, Amy, Hull, Diana, Ahmadhaider, Nafeesah, Bates, Michelle, McGhee, Christopher, Ellis, Hannah, Howe, Gwenllian Sera, Singh, Jayaprakash, Stroud, Natalie, Roche, Lisa, Lynch, Ceri, Deacon, Bethan, Pothecary, Carla, Smeaton, Justyna, Agravante, Kevin, Krishnamurthy, Vinodh, Diaba, Cynthia, John, Lincy, Lim, Lai, Jha, Rajeev, Egan, Jasmine, Felton, Timothy, Glasgow, Susannah, Padden, Grace, Choudhr, Ozerah, Bradley-Potts, Joanne, Moss, Stuart, Lingeswaran, Saejohn, Alexander, Peter, Brandwood, Craig, Fiouni, Sofia, Ward, Luke, Allen, Schvearn, Shaw, Jane, Smith, Christopher, Adanini, Oluronke, Collins, Rebecca, Msiska, Maines, Ofori, Linda, Bhatia, Nikhil, Dolan, Hayley, Brunton, Mark, Caterson, Jess, Coles, Holly, Keating, Liza, Tilney, Emma, Jacques, Nicola, Frise, Matthew, Armistead, Jennifer, Bartley, Shauna, Bhuie, Parminder, Rai, Sabi, Tomkova, Gabriela, Greer, Sandra, Shuker, Karen, Tridente, Ascanio, Dobson, Emma, Hunt, Jodie, Tully, Redmond, Dearden, Joy, Drummond, Andrew, Kamath, Prakash, Bullock, Emily, Mulcahy, Michelle, Munt, Shelia, O’Connor, Grainne, Philbin, Jennifer, Rishton, Chloe, Scott, Chloe, Winnard, Sarah, Hasni, Nurkamalia, Gascoyne, Rachel, Hawes, Joanne, Pritchard, Kelly, Stevenson, Lesley, Whileman, Amanda, Beavis, Sarah, Bishop, Lauren, Cart, Cindy, Dale, Katie, Kelly-Baxter, Mary, Mendelski, Adam, Moakes, Emma, Smith, Rheanna, Woodward, Jan, Wright, Stephanie, Allan, Angela, Botello, Adriana, Liew, Jade, Medhora, Jasmine, Trumper, Erin, Savage, Felicity, Scott, Teresa, Place, Marc, Kaye, Callum, Benyon, Sarah, Marriott, Suzie, Park, Linda, Quinn, Helen, Skyes, Daisy, Zitter, Lily, Baines, Kizzy, Gordon, Elizabeth, Keenan, Samantha, Pitt, Andrew, Duffy, Katharine, Ireland, Jane, Semple, Gary, Turner, Lynne, Cathcart, Susanne, Rimmer, Dominic, Puxty, Alex, Puxty, Kathryn, Hurst, Andrew, Miller, Jennifer, Speirs, Susan, Walker, Lauren, Bradshaw, Zena, Brown, Joanna, Melling, Sarah, Preston, Stephen, Slawson, Nicola, Warden, Scott, Beasley, Alanna, Stoddard, Emma, Benham, Leonie, Cupitt, Jason, Caswell, Melanie, Elawamy, Lisa, Wignall, Ashleigh, Roberts, Belinda, Golding, Hannah, Leggett, Samantha, Male, Michelle, Marani, Martyna, Prager, Kirsty, Williams, Toran, Golder, Kim, Jones, Oliver, Cusack, Rebecca, Bolger, Clare, Burnish, Rachel, Carter, Michael, Jackson, Susan, Salmon, Karen, Biss, Jonathan, Aquino, Maia, Croft, Maria, Frost, Victoria, White, Ian, Govender, Keshnie, Webb, Natasha, Stapleton, Liana, Wells, Colin, Nikitas, Nikitas, Sanchez - Rodriguez, Ana, Spencer, Kayleigh, Stowe, Bethan, Izzard, Yvonne, Poole, Michelle, Monnery, Sonja, Trotman, Sallyanne, Beech, Valerie, Combes, Edward, Joefield, Teishel, Covernton, Patrick, Savage, Sarah, Woodward, Elizabeth, Camsooksai, Julie, Reschreiter, Henrik, Barclay, Charlotte, DeAth, Yasmin, Dube, Judith, Humphrey, Charlotte, Jenkins, Sarah, Langridge, Emma, Milne, Rebecca, Wadams, Beverley, Woolcock, Megan, Brett, Michael, Digby, Brian, Gemmell, Lisa, Hornsby, James, MacGoey, Patrick, O’Neil, Pauline, Price, Richard, Sundaram, Radha, Rodden, Natalie, Thomson, Nicola, Rooney, Kevin, Currie, Susan, Henderson, Philip, Ogg, Bethan, Whiteley, Simon, Wilby, Liz, Long, Kate, Matthew, Shailamma, Salada, Sheila, Trott, Susan, Watts, Sarah, Friar, Zoe, Speight, Abigail, Bastion, Victoria, Chandna, Humza, Djeugam, Brice, Haseeb, Muhammad, Kent, Harriet, Lubimbi, Gamu, Murdoch, Sophie, Thomas, Alastair, David, Beena, Lorusso, Rachel, Vochin, Ana, Penacerrada, Melchizedek, Wulandari, Retno, Heath, Charlotte, Jakkula, Srinivas, Morris, Anna, Ahmed, Ashar, Nune, Arvind, Buttriss, Claire, Whitaker, Emma, Davey, Miriam, Golden, David, Acklery, Amy, Fernandes, Fabio, Seaman, Bec, Earl, Victoria, Collins, Amy, Khaliq, Waqas, Adam, Rachel, Treus, Estefania, Holland, Sarah, Alfonso, Jordan, Blackledge, Bethan, Bruce, Michelle, Durrans, Laura Jayne, Eltayeb, Ayaa, Harris, Jade, Hey, Samuel, Hruska, Martin, Lamb, Thomas, Rothwell, Joanne, Fitzgerald, Adele, Lindergard, Gabriella, T-Michael, Helen, Duncan, Tracey, Baxter-Dore, Sharon, Cooper, Lisa, Fox, Claire, Guerin, Jacinta, Hodgkiss, Tracey, Connolly, Karen, McAlinden, Paul, Bridgett, Victoria, Fearby, Maggie, Gulati, A., Hanson, Helen, Kelly, Sinead, McCormack, Louise, Nixon, Rachel, Robinson, Philip, Slater, Victoria, Stephenson, Elaine, Webster, Andrea, Webster, K., Hays, Carole, Hudson, Anne, Patel, Bijal, Clement, Ian, Davis, John, Francis, Sarah, Jerry, Douglas, Abernathy, Caroline, Foster, Louise, Gratrix, Andrew, Cabral-Ortega, Llucia, Hines, Matthew, Martinson, Victoria, Stones, Elizabeth, Winter, Karen, Barrow, Esther, Wylie, Katharine, Baines, Deborah, Birchall, Katie, Kolakaluri, Laurel, Clark, Richard, Sukumaran, Anila, Barker, Melanie, Paripoorani, Deborah, Smith, Lara, Taylor, Charlotte, Downes, Charlotte, Hayman, Melanie, Riches, Katie, Daniel, Priya, Subramanian, Deepak, Holding, Kathleen, Hilton, Mary, Mcdonald, Carly, Richardson, Georgina, Halladay, Georgia, Harding, Peter, Reddy, Amie, Turner-Bone, Ian, Wilding, Laura, Parker, Robert, Lloyd, Michaela, Smith, Leanne, Kelly, Charlie, Lazo, Maria, Neal, Alan, Walton, Olivia, Melville, Julie, Naisbitt, Jay, Joseph, Rosane, Callam, Sara, Hudig, Lisa, Keshet-Price, Jocelyn, Stammers, Katie, Convery, Karen, Randell, Georgina, Fottrell-gould, Deirdre, Mwaura, Esther, Sutherland, Sara-Beth, Stewart, Richard, Mew, Louise, Wren, Lynn, Thrasyvoulou, Laura, Willis, Heather, Hopkins, Bridget, Lenton, Daniel, Roberts, Abigail, Bokhari, Maria, Lucas, Rachael, McCormick, Wendy, Ritzema, Jenny, Linnett, Vanessa, Sanderson, Amanda, Wild, Helen, Flanagan, Rebecca, Hull, Robert, Rhead, Kat, McKenna, Emma, Hughes, Gareth, Anderson, Jennifer, Jones, Kelly, Latham, Scott, Riley, Heather, Coulding, Martina, Clark, Martyn, McCormick, Jacqueline, Mercer, Oliver, Potla, Darsh, Rehman, Hafiz, Savill, Heather, Turner, Victoria, Jude, Edward, Kilroy, Susan, Apetri, Elena, Basikolo, Cathrine, Catlow, Laura, Collis, Matthew, Doonan, Reece, Harvey, Alice, Knowles, Karen, Lee, Stephanie, Lomas, Diane, Lyons, Chloe, McMorrow, Liam, Michael, Angiy, Pendlebury, Jessica, Perez, Jane, Poulaka, Maria, Proudfoot, Nicola, Slevin, Kathryn, Thomas, Vicky, Walker, Danielle, Dark, Paul, Charles, Bethan, McLaughlan, Danielle, Slaughter, Melanie, Horner, Dan, Marsden, Tracy, Andrews, Joyann, Beech, Emily, Akinkugbe, Olugbenga, Bamford, Alasdair, Belfield, Holly, Jones, Gareth A. L., McHugh, Tara, Meghari, Hamza, Ray, Samiran, Tomas, Ana Luisa, O’Neill, Lauran, Peters, Mark, Bell, Michael, Benkenstein, Sarah, Chisholm, Catherine, Davies, Charlene, Kupiec, Klaudia, Payne, Caroline, Halls, Joanna, Blakemore, Hayley, Goff, Elizabeth, Hayes, Kati, Smith, Kerry, Stephens, Deanna, Worner, Ruth, Borislavova, Borislava, Faulkner, Beverley, Thomas, Matt, Cookson, Ruth, Gendall, Emma, Larman, Georgina, Pope, Rebecca, Smalira, Artur, Priestley, Victoria, Cosier, Tracey, Millen, Gemma, Rand, James, Schumacher, Natasha, Sandhar, Roxana, Weston, Heather, Richardson, Neil, Cooper, Lucy, Jones, Cathy, Huang, Ya-Wen Jessica, Jacob, Reni, Denmade, Craig, Mcintyre, Lewis, Trodd, Dawn, Martin, Jane, Watson, Geoff, Bevan, Emily, Wreybrown, Caroline, Bano, Shereen, Bellwood, Ruth, Bentley, Michael, Bromley, Matt, Gurr, Lucy, Ledgard, Camilla, McGowan, Janet, Pye, Kate, Sellick, Kirsten, Stacey, Amelia, Warren, Deborah, Wilkinson, Brian, Akeroyd, Louise, Shafique, Huma, Morgan, James, Shorter, Susan, Swinger, Rachel, Waters, Emily, Lawton, Tom, Allan, Elizabeth, Darlington, Kate, Davies, Ffyon, Davies, Llinos, Easton, Jack, Kumar, Sumit, Lean, Richard, Mackay, Callum, Pugh, Richard, Qiu, Xinyi, Rees, Stephanie, Scanlon, Jeremy, Lewis, Joanne, Menzies, Daniel, Bolger, Annette, Davies, Gwyneth, Davies, Jennifer, Garrod, Esther, Jones, Helen, Manley, Rachel, Williams, Hannah, Frankham, Jordan, Pitts, Sally, White, Nigel, Branney, Debbie, Tiller, Heather, Efford, Georgia, Garland, Zoe, Grimmer, Lisa, Gumbrill, Bethany, Johnson, Rebekah, Sweet, Katie, Bewley, Jeremy, Coleman, Christina, Corcoran, Katie, Morano, Eva Maria Hernandez, Shiel, Rachel, Webster, Denise, Bonnici, Josephine, Daniel, Eleanor, Dell, Abbie, Kent, Melanie, Wilkinson, Ami, Brown, Ellen, Kay, Andrea, Campbell, Suzanne, Cowton, Amanda, Birt, Mark, Greenaway, Vicki, Potts, Kathryn, Hutton, Clare, Shepperson, Andrew, Forsey, Miranda, Nicholson, Alice, Vertue, Mark, Riches, Joanne, Kaliappan, Agilan, Nicholson, Anne, MacCallum, Niall, Raith, Eamon, Bercades, Georgia, Hass, Ingrid, Brealey, David, Martir, Gladys, Reyes, Anna, Smyth, Deborah, Zapatamartinez, Maria, Alvaro, Ana, Jetha, Champa, Ma, Louise, Booker, Lauren, Mostoles, Loreta, Pratley, Anezka, Altabaibeh, Abdelhakim, Parmar, Chetan, Gilbert, Kayleigh, Ferguson, Susie, Shepherd, Amy, Morris, Sheila, Baruah, Rosie, Lloyd, Georgina, Bell, Stephanie, Rivers, Vanessa, Purewal, Bally, Hammerton, Kate, Anderson, Susan, Birch, Janine, Collins, Emma, Oleary, Ryan, Cornell, Sarah, Jarmain, Jordan, Rogerson, Kimberley, Wakinshaw, Fiona, Woods, Lindsey, Rostron, Anthony, Elcioglu, Zeynep, Roy, Alistair, Bell, Gillian, Dickson, Holly, Wilcox, Louise, Katary, Amro, English, Katy, Hutter, Joanne, Pawley, Corinne, Doble, Patricia, Shovelton, Charmaine, Vaida, Marius, Purnell, Rebecca, Thomas, Ashly, Cagova, Lenka, Fofano, Adama, Holcombe, Helen, Mitchell, Alice Michael, Mwaura, Lucy, Praman, KrithivasanÂ, Garnr, Lucie, Mepham, Sue, Paques, Kitty, Vuylsteke, Alain, Mackie, Jennifer, Pearn, Carmen, Zamikula, Julie, Nyirenda, Maggie, Capozzi, Lisa, Reece-Anthony, Rosie, Noor, Hazma, Nilo, Alfa Cresia, Grove, Michelle, Daniel, Amelia, Finn, Joanne, White, Nikki, Saha, Rajnish, Badal, Bibi, Ixer, Karen, Duffin, Donna, Player, Ben, Hill, Helen, Cole, Jade, Brooks, Jenny, Davies, Rhys, Hunt, Lauren, Thomas, Emma, Williams, Angharad, Oblak, Metod, Thankachen, Mini, Irisari, Jamie, Sayan, Amrinder, Popescu, Monica, Finch, Cheryl, Jamieson, Andrew, Quinn, Alison, Cooper, Joshua, Liderth, Sarah, Waddington, Natalia, Burn, Iona, Manso, Katarina, Penn, Ruth, Tebbutt, Julie, Thornton, Danielle, Winchester, James, Hambrook, Geraldine, Shanmugasundaram, Pradeep, Craig, Jayne, Simpson, Kerry, Higham, Andrew, Sibbett, Louise, Paine, Sheila, Reed, Annabel, Conyngham, Jo-Anna, Mupudzi, Mcdonald, Thomas, Rachel, Wright, Mary, Griffin, Denise, Partridge, Richard, Corral, Maria Alvarez, Muchenje, Nycola, Sitonik, Mildred, Butler, Aaron, Folkes, Linda, Fox, Heather, Gardner, Amy, Helm, David, Hobden, Gillian, King, Kirsten, Margalef, Jordi, Margarson, Michael, Martindale, Tim, Meadows, Emma, Raynard, Dana, Thirlwall, Yvette, Baird, Yolanda, Gomez, Raquel, Martin, Darren, Hodgson, Luke, Corin, Clinton, Sidall, Erikka, Szabo, Densie, Floyd, Sharon, Davies, Hannah, Austin, Karen, Kelsall, Olivia, Wood, Hannah, Cornell, Thomas, Ralph, Kate, Bean, Sarah, Burt, Karen, Spivey, Michael, Richards, Carol, Tedstone, Rachel, Carmody, Siobhain, Zhao, Xiaobei, Page, Valerie, Guanco, Mark Louie, Hoxha, Elvira, Zorloni, Camilla, Dean, Charlotte, Jones, Emma, Carter, Emma, Dunn, Joshua, Kong, Thomas, Mahenthran, Mervin, Marsh, Chris, Holland, Maureen, Keenan, Natalie, Mahmoud, Mohamed, Lyons, Marc, Wassall, Helen, Young, Meghan, Bradley, Paul, Burda, Dorota, Donlon, Sinead, Harden, Lesley, Harris, Celia, Mayangao, Irving, Montaser, Rugia, Mtuwa, Sheila, Piercy, Charles, Smith, Eleanor, Stone, Sarah, Verula, Jerik, Blackman, Helen, Marriott, Cheryl, Michalak, Natalia, Creagh-Brown, Ben, Salberg, Armorel, Boyer, Naomi, Pristopan, Veronika, Maynard, Victoria, Walker, Rachel, Hormis, Anil, Collier, Dawn, Graham, Cheryl, McCormick, Jake, Warrington, Jake, Cosgrove, Denise, McFarland, Denise, Ratcliffe, Judith, Charnock, Rob, Wynter, Inez, Gill, Mandy, Kirk, Jill, Paul, Paul, Ratnam, Valli, Shelton, Sarah, Jardine, Catherine, Hay, Alasdair, Williams, Dewi, Durga, Latha, Hibbert, Meg, Kennard-Holden, Gareth, Woodford, Chrsitopher, Tetla, Dariusz, Price, Alicia, Thomas, Alice, Thorpe, Chris, Knights, Ellen, Ward, Donna, Laha, Shondipon, Verlander, Mark, Williams, Alexandra, Prout, Rachel, Langton, Helen, Watters, Malcolm, Hunt, Charlotte, Novis, Catherine, Arif, Sarwat, Cunningham, Amy, Hewitt, Claire, Hindale, Julia, Jackson-Lawrence, Karen, Shepardson, Sarah, Wills, Maryanne, Butler, Susie, Tavares, Silivia, Barber, Russell, Hilldrith, Annette, Hubbard, Kelly, Egginton, Dawn, Clark, Michele, Purvis, Sarah, Sinclair, Simon, Collins, Vicky, Landeg, Bethan, Sell, Craig, Coetzee, Samantha, Gales, Alistair, Otahal, Igor, Icke, Becky, Raj, Meena, Williams, Caroline, Williams, Jill, Hill, Lucy, Kayani, Abdul, Masunda, Bridgett, Gondo, Prisca, Atayeva, Nigara, Cruz, Carina, Pattison, Natalie, Burnett, Caroline, Hatton, Jonathan, Heeney, Elaine, Newton, Maria, Al-Moasseb, Hassan, Behan, Teresa, Player, Jasmine, Stead, Rachael, Mitra, Atideb, Nauyokas, Kirsty, Humphreys, Sally, Cockerill, Helen, Tampsett, Ruth, Postovalova, Evgeniya, Coventry, Tina, McGregor, Amanda, Fowler, Susan, Macmahon, Mike, Cochrane, Patricia, Pirie, Sandra, Hanley, Sarah, Ali, Asifa, Brady, Megan, Dale, Sam, Dance, Annalisa, Gledhill, Lisa, Greig, Jill, Hanson, Kathryn, Holdroyd, Kelly, Home, Marie, Ishaq, Tahira, Kelly, Diane, Matapure, Lear, Melia, Deborah, Mellor, Samantha, Merwaha, Ekta, Nortcliffe, Tonicha, Shaw, Lisa, Shaw, Ryan, Wood, Tracy, Bayo, Lee-Ann, Usher, Miranda, Wilson, Alison, Kitson, Ross, Pinnell, Jez, Robinson, Matthew, Boltwood, Kaitlin, Birch, Jenny, Bough, Laura, Tutton, Rebecca, Winter-Goodwin, Barbara, Goodsell, Josie, Taylor, Kate, Williams, Patricia, Williams, Sarah, Cave, Ashleigh, Rees, James, Imeson-Wood, Janet, Smith, Jacqueline, Amin, Vishal, Karthik, Komala, Kausar, Rizwana, Anastasescu, Elena, Reid, Karen, Anumakonda, Vikram, Stoddart, Ella, Demetriou, Carrie, Eckbad, Charlotte, Howie, Lucy, Mitchard, Sarah, Ramos, Lidia, White, Katie, Hierons, Sarah, Kelly, Fiona, Serrano-Ruiz, Alfredo, Evans, Gabrielle, Nicol, Liz, Wilkins, Joy, Hulacka, Kim, Debreceni, Gabor, Brown, Alison, Crickmore, Vikki, Hill, Kay, Kannan, Thogulava, Dagutao, Zenaida, Beesley, Kate, Lewis, Alison, Perry, Jess, Antony, Sherly, Board, Sarah, Buckley, Clare, Pippard, Lucy, Tanate, Alfonso, Wood, Diane, Kubisz-Pudelko, Agnieska, Gouda, Ayman, Auld, Fiona, Donnachie, Joanne, Murdoch, Euan, Prentice, Lynn, Runciman, Nikole, Senaratne, Dhaneesha, Short, Abigail, Sweeney, Laura, Symon, Lesley, Todd, Anne, Turner, Patricia, McCann, Erin, Salutous, Dario, Edmond, Ian, Whitelaw, Lesley, Bland, Yvonne, Kajtor, Istvan, Kavanagh, Lisa, Singler, Karen, Linfield-Brown, George, Moore, Luke Stephen Prockter, Vizcaychipi, Marcela, Martins, Laura, Moore, Luke, Bull, Rhian, Carungcong, Jaime, Allen, Louise, Beranova, Eva, Knight, Alicia, Price, Carly, Tilbey, Sorrell, Turney, Sharon, Hazelton, Tracy, Tutt, Gabriella, Arora, Mansi, Turki, Salah, Sinfield, Emily, Deery, Joanne, Ramos, Hazel, Cristiano, Daniele, Dormand, Natalie, Farzad, Zohreh, Gummadi, Mahitha, Salmi, Sara, Sloane, Geraldine, Varghese, Mathew, Thwaites, Vicky, Patel, Brijesh, Kamal, Liyanage, Zborowski, Anelise Catelan, Coe, Ryan, Anderson, Madeleine, Beadle, Jane, Coates, Charlotte, Collins, Katy, Crowley, Maria, Johnson, Laura, King, Laura, Paramsothy, Remi, Sargeant, Janet, Silva, Pedro, Stuart, Carmel, Taylor, June, Tyl, David, Wakefield, Phillipa, Kamundi, Charlotte, Olufuwa, Olumide, Belagodu, Zakaulla, Gherman, Anca, Oakley, Naomi, Allan, John, Geary, Tim, Meikle, Alistair, O’Brien, Peter, Wood, Stephen, Clark, Andrew, Houston, Gordon, Black, Karen, Clarkson, Michelle, D’Sylva, Stuart, Morrison, Alan, Norman, Kathryn, Taylor, Margaret, Clements, Suzanne, Cohrane, Catriona, Gonzalez, Nora, Strachan, Dominic, Beith, Claire, Moar, Kirsten, Anderson, Peter, Archer, Katie, Burtenshaw, Andrew, Clayton, Sarah, Cother, Naiara, Cowley, Nicholas, Davis, Caroline, Digby, Stephen, Durie, Alison, Harrison, Alison, Low, Emma, McAlindon, Michael, McCurdy, Alex, Morgan, Aled, Rankin, Tobias, Thrush, Jessica, Tranter, Helen, Vigurs, Charlie, Wild, Laura, Murphy, Lorna, Smythe, Michelle, Brickell, Kathy, Ali, Inthakab Ali Mohamed, Beaumont, Karen, Elsaadany, Mohamed, Fernandes, Kay, Ally, Sameena Mohamed, Rangarajan, Harini, Sarathy, Varun, Selvanayagam, Sivarupan, Vedage, Dave, White, Matthew, Coton, Zoe, Joshy, Aricsa, Blunt, Mark, Curgenven, Hollie, Botfield, Liam, Dexter, Catherine, Kuravi, Aditya, Butler, Joanne, Chadwick, Robert, Ranga, Poonam, Richardson, Lisa, Virgilio, Emma, Anwer, Maddiha, Garg, Atul, Botfield, Donna, Marriott, Xana, Stewart, Keely, Mullan, Dee, Gaylard, Jane, Nowak, Justyna, Jones, Sian, Crawley, Rikki, Crew, Abigail, Cunningham, Mishell, Daniels, Allison, Harrison, Laura, Hope, Susan, Lancaster, Nicola, Matthews, Jamie, Wray, Gemma, Inweregbu, Ken, Cutts, Sarah, Miller, Katharine, Brady, Ailbhe, Chan, Rebekah, McIvor, Shane, Prady, Helena, Mathew, Bijoy, Little, Jeff, Furniss, Tim, Wright, Chris, King, Bernadette, Wasson, Christopher, O’Neill, Aisling, Turley, Christine, McGuigan, Peter, Collins, Erin, Finn, Stephanie, Green, Jackie, McAuley, Julie, Nair, Abitha, Quinn, Charlotte, Tauro, Suzanne, Ward, Kathryn, McGinlay, Michael, Reddy, Kiran, Ahmad, Norfaizan, Anderson, Samantha, Barker, Joann, Bauchmuller, Kris, Birchall, Kathryn, Bird, Sarah, Cawthron, Kay, Chetam, Luke, Cole, Joby, Donne, Ben, Foote, David, Ford, Amber, Hanratty, Helena, Harrington, Kate, Hesseldon, Lisa, Housley, Kay, Jackson, Yvonne, Jarman, Claire, Kibutu, Faith, Lenagh, Becky, Macharia, Irene, Masuko, Shamiso, Milner, Leanne, Newell, Helen, Nwafor, Lorenza, Oxspring, Simon, Phillips, Patrick, Raithatha, Ajay, Rowland-Jones, Sarah, Smith, Jacqui, Thompson, Roger, Trower, Helen, Walker, Sara, Watson, James, Wiles, Matthew, Lye, Alison, Willson, Jayne, Mills, Gary, Harris, Sansha, Hartill, Eleanor, Barron, Anthony, Collins, Ciara, Kaul, Sundeep, Nolan, Claire, Polgar, Oliver, Prendergast, Claire, Rogers, Paula, Shokkar, Rajvinder, Woodruff, Meriel, Mahay, Kanta, Reed, Anna, Meyrick, Hayley, Passmore, Heather, Farwell, James, O’Connell, Susan, Gregory, Jane, Barberis, Luigi, Harper, Rosemary, Smith, Tim, Armstrong, Diane, Bowey, Angie, Cowley, Anne, Corner, Andrew, Highgate, Judith, Rutherfurd, Claire, Taylor, Jo-Anne, Goodwin, Sarah, Eapen, Beena, Trim, Fiona, Donnison, Phil, Armstrong, Lisa, Bates, Hayley, Dooks, Emma, Farquhar, Fiona, Kitching, Amy, McParland, Chantal, Packham, Sophie, Hairsine, Brigid, Andreou, Premetie, Hales, Dawn, Mathews, Megha, Patel, Rekha, Barry, Peter, Flint, Neil, Hailstone, Jessica, Ghuman, Navneet, Leonard, Bethany, Lees, Rachel, Butcher, Deborah, Leng, Katy, Butterworth-Cowin, Nicola, O’Sullivan, Susie, Ghosh, Alison, Williams, Emma, Adams, Colene, Agasou, Anita, Arden, Tracie, Beekes, Mandy, Bowes, Amy, Boyle, Pauline, Button, Heather, Carnahan, Mandy, Carter, Anne, Childs, Danielle, Hurford, Fran, Hussain, Yasmin, Javaid, Ayesha, Jones, James, Leigh, Michael, Martin, Terry, Millward, Helen, Motherwell, Nichola, Newman, Julie, Rikunenko, Rachel, Stickley, Jo, Summers, Julie, Ting, Louise, Tivenan, Helen, Donaldson, Denise, Capps, Nigel, Cale, Emily, Jose, Sanal, Osbourne, Wendy, Pajak, Susie, Rankin, Jayne, Tonks, Louise, Baird, Tracy, Harkins, Margaret, Ruddy, Jim, West, Joe, Duffield, Joseph, Mallon, Lewis, Smith, Oliver, Smuts, Sara, Campbell, Andy, Davies, Cate, Davies, Sarah, Hughes, Rachel, Jobes, Lisa, Whitehead, Victoria, Watkins, Clare, Bowman, Fiona, Milligan, Barry, McPherson, Liane, Metherell, Stella, Harris, Nichola, Lake, Victoria, Radford, Elizabeth, Smallwood, Andy, Gopal, Shameer, Vassell, Katherine, Bell, Dina, Boyle, Rosalind, Douglas, Katie, Glass, Lynn, Lennon, Liz, Rattray, Austin, Lee, Emma, Jones, Danielle, Parsons, Penny, Attwood, Ben, Jefferson, Paul, Ranganathan, Mohan, Atwal, Inderjit, Campbell, Bridget, Day, Angela, Stagg, Camilla, Haynes, Emma, Ahmed, Cecilia, Clamp, Sarah, Colley, Julie, Haq, Risna, Hayes, Anne, Joseph, Sibet, Maqsood, Zahira, Hussain, Samia, Hulme, Jonathan, Domingos, Patience, Kumar, Rita, Purewal, Manjit, Taylor, Becky, Bunni, Lara, Latif, Monica, Jennings, Claire, Jose, Shilu, Marshall, Rebecca, Metryka, Aleksandra, Subramanian, Gayathri, Burgoyne, Adam, Tyler, Amanda, Waldron, Joanne, Hilltout, Paula, Evitts, Jayne, Ward, Geraldine, Bremmer, Pamela, Hawkins, Carl, Jackman, Sophie, Ogorek, Michal, Ashby, Kylie, Thornton, Lorraine, Mercer, Pauline, Halkes, Matthew, Revill, Adam, Saint, Bryony, Fletcher, Jo, Netherton, Kimberley, Chablani, Manish, Kirkby, Amy, Roper, Amanda, Szymiczek, Kinga, Sutherland, Isobel, O’Brien, Linda, Connell, Joanne, Davies, Kim, Lewis, Tracy, Omar, Zohra, Perkins, Emma, Sathe, Sonia, Davies, Ellie, Lyon, Alex, Mapfunde, Isheunesu, Willis, Charlotte, Hitchcock, Rachael, Hall, Kathryn, King, Christopher, Fagan, Andrew, Nazari, Roonak, Worsley, Lucy, Allibone, Suzanne, Kasipandian, Vidya, Patel, Amit, Cutting, Parisa, Genetu, Roman, Mac, Ainhi, Murphy, Anthony, Ward, Sinead, Butt, Fatima, Ayers, Amanda, Harrison, Wendy, Mackintosh, Katherine, North, Julie, Ashton, Lydia, Bi, Rehana, Owen, Samantha, Winmill, Helen, Scholefield, Barney, Blowing, Hannah, Williams, Erin, Duskova, Michaela, Edwards, Michelle, Rees, Alun, Thomas, Helen, Brooks, Jolene, Phipps, Janet, Brooks, Suzanne, Dennis, Catherine, Parris, Vicki, Srikaran, Sinduya, Sukha, Anisha, McGregor, Alistair, Tiongson, Gerlynn, Adams, Katie, Andrew, Benedict, Brayne, Adam, Carter, Sasha, Findlay, Louise, Fisher, Emma, Jackson, Peter, Kaye, Duncan, Parkin, Juliet, Tuckey, Victoria, Hunt, Jane, Love, Nicholas, van Koutrick, Lynne, Hanson, Ashley, Dent, Kathy, Horsley, Elizabeth, Pearson, Sandra, Spencer, Sue, Hutchinson, Dorothy, Potoczna, Dorota, Akhtar, Muhammad Nauman, Cottam, Lisa-Jayne, Sanders, Jack, Garcia, Sara Mingo, pakou, Glykeria, Filipe, Helder, Maharajh, Amitaa, de Neef, Mark, Martin, Daniel, Eastgate, Christine, Teoh, Poh Choo, Barrett, Fiona, Bradley, Clare, Donaldson, Avril, Mascarenhas, Mairi, O’Hara, Marianne, Okeefe, Laura, Clarke, Noreen, Whiteside, Jonathan, Campbell, Rachael, Matheson, Joanna, McDonald, Deborah, Patience, Donna, Rice, Polly, Clapham, Melanie, Mutch, Rachel, Craig, Hannah, Poultney, Una, Burns, Karen, Twiss, Sophie, Barton, Janet, George, Linsha, Harrop, Clare, Mathew, Sherly, Wright, David Justin, Harrison, Rachel, Toohie, Jordan, Chandler, Ben, Turnbull, Alison, Mallinson, Janine, Elliott, Kerry, Wolf-Roberts, Rebecca, Tench, Helen, Hobrok, Maria, Loosley, Ronda, McGuinness, Heather, Sims, Tanya, Afolabi, Deborah, Allison, Kathryn Sian, Anderson, Taya, Dore, Rachael, Jones, Dawn, Rogers, Naomi, Saunderson, Paula, Whitbread, Jennifer, O’Malley, Laura, Rad, Laura, Hawcutt, Daniel, Aldridge, Jonathan, Tolson, Melanie, Garrioch, Sweyn, Tomlinson, Joanne, Grosdenier, Michael, Loader, David, Kapoor, Ritoo, Hector, Gemma, Scherewode, Joslan, Sri-Chandana, Chunda, Stephenson, Lorraine, Marsh, Sarah, Rosa, Arnold Dela, Jhanji, Shaman, Bemand, Thomas, Howle, Ryan, Baikady, Ravishankar Rao, Thomas, Benjamin, Black, Ethel, Tatham, Kate, Gurram, Sambasivarao, Watson, Ekaterina, Quaid, Sheena, Saunderson, Anne, O’Brien, Rachel, Moultrie, Sam, Service, Jen, Cheyne, Clare, Odam, Miranda, Wiliams, Alison, Barnes, Nicky, Csabi, Peter, Rocha, Joana Da, Glynou, Louika, Huffenberger, Amy, Bryant, Jade, Pickard, Amy, Roe, Nicholas, Bellini, Arianna, Mayer, Anton, Burrow, Amy, Colley, Natalie, Evans, Jayne, Howlett, Alex, Khalifeh, Zeinab, Pryce, Jerldine, Gorman, Claire, Brady, Rebecca, Timlick, Elizabeth, Antoine, Pierre, Gupta, Abhinhav, Hardy, John, Houlden, Henry, Moncur, Eleanor, Tucci, Arianna, Tariq, Ambreen, Tagliavini, Emma, Ramsay, Becky, Fidler, Katy, Donnelly, Kevin, Hollis, Rebecca, Barr, Jocelyn, Boyd, Elizabeth, Irvine, Val, Shelley, Ben, Buckley, Julie, Hamilton, Charlene, Valdeavella, Kathryn, Bircham, Sarah, Liggett, Steven, Patil, Anand, Siddiq, Afshan, Goddard, Peter, Donovan, Sally, Zainy, Tala, Maleady-Crowe, Fiona, Todd, Linda, Salehi, Shahla, Elgar, Greg, Chan, Georgia, Arumugam, Prabhu, Patch, Christine, Rendon, Augusto, Bentley, David, Kingsley, Clare, Fowler, Tom A., Elliott, Paul, Tenesa, Albert, Aitkin, Emma, Aravindan, Latha, Armstrong, Ruth, Biggs, Heather, Boz, Ceilia, Brown, Adam, Chikowore, Primmy, Coutts, Audrey, Coyle, Judy, Cullum, Louise, Das, Sukamal, Day, Nicky, Donnelly, Lorna, Duncan, Esther, Finernan, Paul, Fourman, Max Head, Furlong, Anita, Furniss, James, Gallagher, Bernadette, Gilchrist, Tammy, Golightly, Ailsa, Hafezi, Katarzyna, Hamilton, Debbie, Hendry, Ross, Kearns, Naomi, Law, Dawn, Law, Rachel, Law, Sarah, Lidstone-Scott, Rebecca, Lauder, Christen, Macgillivray, Louise, Maclean, Alan, Mal, Hanning, McCafferty, Sarah, Mcmaster, Ellie, Meikle, Jen, Moore, Shona C., Murphy, Sheena, Mybaya, Hellen, Oosthuyzen, Wilna, Zheng, Chenqing, Chen, Jiantao, Paterson, Trevor, Tucker, Petra, Schon, Katherine, Stenhouse, Andrew, Das, Mihaela, Swets, Maaike, Szoor-McElhinney, Helen, Taneski, Filip, Turtle, Lance, Wackett, Tony, Ward, Mairi, Weaver, Jane, Wrobel, Nicola, Rakitko, Alexander, Ilinsky, Valery, Yermakovich, Danat, Popov, Iaroslav, Chernitsov, Alexander, Kovalenko, Elena, Vergasova, Ekaterina, Prokhorov, Alexandr, Krasnenko, Anna, Plotnikov, Nikolay, Stetsenko, Ivan, Kim, Anna, Cirulli, Elizabeth T., Schiabor Barrett, Kelly M., Bolze, Alexandre, White, Simon, Washington, Nicole L., Lu, James T., Riffle, Stephen, Tanudjaja, Francisco, Wang, Xueqing, Ramirez, Jimmy M., Leonetti, Nicole, Sandoval, Efren, Neveux, Iva, Dabe, Shaun, Grzymski, Joseph J., Joshi, Madhvi N., Dixit, Raghav D., Shah, Pranay K., Upadhyay, Kamlesh J., Chuhan, Naresh T., Desai, Kairavi J., Shah, Meenakshi R., Modi, Bhavesh, Joshi, Chaitanya G., Pandit, Ramesh J., Singh, Indra, Ansari, Afzal I., Raval, Janvi N., Patel, Zarna Z., Moreno-Estrada, Andres, Vázquez-Pérez, Joel Armando, Castillejos-López, Manuel, Aquino-Gálvez, Arnoldo, Shamah-Levy, Teresa, Ávila-Arcos, María C., Luna, María Teresa Tusié, Hidalgo-Miranda, Alfredo, Barberena-Jonas, Carmina, Quinto-Cortés, Consuelo D., Ávila-Arcos, Marco Antonio, Huerta-Chagoya, Alicia, García-García, Lourdes, Barnetche, Jesús Martinez, Alpuche-Aranda, Celia, Rivera, Juan A., Gutiérrez, Tonatiuh Barrientos, Ochoa-Guzmán, Ana, Ordoñez-Sánchez, Maria Luisa, Segura-Kato, Yayoi, Herrera-Montalvo, Luis Alonso, Mendoza-Vargas, Alfredo, Reyes-Grajeda, Juan Pablo, Cruz-Cruz, Alonso D., Velázquez-Cruz, Rafael, Torres-Espíndola, Luz María, Sierra-Vargas, Martha Patricia, Camarena, Angel, Ruiz, Víctor, Chávez-Alderete, Jaime, Jaime-Capetillo, María Esther, Guadarrama-Pérez, Cristóbal, Zúñiga-Ramos, Joaquin, Olivera-Ramírez, Alejandra, Martínez, Miguel Angel López, Serna-Muñoz, Ricardo, Garmendia, Adriana, Namkoong, Ho, Okada, Yukinori, Imoto, Seiya, Katayama, Kazuhiko, Fukunaga, Koichi, Kitagawa, Yuko, Sato, Toshiro, Hasegawa, Naoki, Kumanogoh, Atsushi, Kimura, Akinori, Ai, Masumi, Tokunaga, Katsushi, Kanai, Takanori, Miyano, Satoru, Ogawa, Seishi, Edahiro, Ryuya, Sonehara, Kyuto, Shirai, Yuya, Ishii, Makoto, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Tanaka, Hiromu, Morita, Atsuho, Lee, Ho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Mikami, Yohei, Tomono, Kazunori, Kato, Kazuto, Matsuda, Fumihiko, Takahashi, Meiko, Hizawa, Nobuyuki, Takeda, Yoshito, Hirata, Haruhiko, Shiroyama, Takayuki, Miyawaki, Satoru, Suzuki, Ken, Maeda, Yuichi, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Takahashi, Kunihiko, Anzai, Tatsuhiko, Hasegawa, Takanori, Ito, Satoshi, Koike, Ryuji, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro, Nakajima, Jun, Nannya, Yasuhito, Omae, Yosuke, Takahashi, Kazuhisa, Harada, Norihiro, Hiki, Makoto, Takagi, Haruhi, Nakamura, Ai, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Ishiguro, Takashi, Takayanagi, Noboru, Isono, Taisuke, Takaku, Yotaro, Takano, Kenji, Anan, Ryusuke, Nakajima, Yukiko, Nakano, Yasushi, Nishio, Kazumi, Ueda, Soichiro, Hayashi, Reina, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Mitamura, Keiko, Saito, Fumitake, Ueda, Tetsuya, Azuma, Masanori, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Yoshiyama, Takashi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Watanabe, Kazuyoshi, Manabe, Tadashi, Ito, Fumimaro, Fukui, Takahiro, Funatsu, Yohei, Koh, Hidefumi, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Saito, Fukuki, Yoshiya, Kazuhisa, Yoshihara, Tomoyuki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Nishi, Koichi, Nishitsuji, Masaru, Tani, Maiko, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Ogura, Takashi, Kitamura, Hideya, Murohashi, Kota, Nakachi, Ichiro, Baba, Rie, Arai, Daisuke, Fuke, Satoshi, Saito, Hiroshi, Kuwahara, Naota, Fujiwara, Akiko, Okada, Takenori, Baba, Tomoya, Noda, Junya, Mashimo, Shuko, Yagi, Kazuma, Shiomi, Tetsuya, Hashiguchi, Mizuha, Odani, Toshio, Mochimaru, Takao, Oyamada, Yoshitaka, Mori, Nobuaki, Izumi, Namiki, Nagata, Kaoru, Taki, Reiko, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Gon, Yasuhiro, Fujitani, Shigeki, Tsuchida, Tomoya, Yoshida, Toru, Kagaya, Takashi, Kita, Toshiyuki, Sakagami, Satoru, Kimizuka, Yoshifumi, Kawana, Akihiko, Nakamura, Yoshihiko, Ishikura, Hiroyasu, Takata, Tohru, Kikuchi, Takahide, Taniyama, Daisuke, Nakamura, Morio, Kodama, Nobuhiro, Kaneyama, Yasunari, Maeda, Shunsuke, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Ito, Akihiro, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Hashimoto, Naozumi, Wakahara, Keiko, Ando, Akira, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Sageshima, Hisako, Nakada, Taka-Aki, Abe, Ryuzo, Shimada, Tadanaga, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Yamasaki, Masaki, Hashimoto, Satoru, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Takada, Minoru, Kanda, Hidenori, Komase, Yuko, Sano, Fumiaki, Asano, Koichiro, Oguma, Tsuyoshi, Harada, Masahiro, Takahashi, Takeshi, Shibusawa, Takayuki, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Izumo, Takehiro, Inomata, Minoru, Awano, Nobuyasu, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Kitagawa, Yuichiro, Yoshida, Shozo, Ogura, Shinji, Nishiyama, Kei, Yoshida, Kousuke, Beppu, Satoru, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Inoue, Yoshiaki, Yamagata, Kunihiro, Chiba, Shigeru, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Shibata, Yoko, Tanino, Yoshinori, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Imamura, Tomonori, Umeda, Akira, Shimada, Hisato, Endo, Mayu, Hayashi, Shinichi, Takahashi, Mai, Nakano, Shigefumi, Yatomi, Masakiyo, Maeno, Toshitaka, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Nishida, Nao, Kawai, Yosuke, Sugiyama, Masaya, Alawneh, Laith M., Maswadeh, Kinda B., Alsoub, Fatima S., AlRawashdeh, Tala J., Esawi, Ezaldeen, Abu Alragheb, Bayan O., Maswadeh, Ahmad B., Al-Kadash, Abdulfattah, Al-Ani, Abdallah, Alsafadi, Dana B., Shahin, Mohammad A., Qtaish, Nuseibah Al, Alawneh, Fade M., Abulail, Joseph A., Zhlawi, Hadi J., Alhousani, Tasneem N., Alzuraiqi, Mohammad R., Al-Ja’afreh, Mohammad M., Allouzy, Sara K., ALjalamdeh, Mothafer, Mansour, Tareq M., Alamer, Lina M., Issa, Ali Banni, Bani younis, Fatima M., Hawari, Feras I., Hayajneh, Wail A., Obeidat, Nathir M., Ahram, Mamoun, Zhlawi, Moh’d Wahib J., Alshaer, Walhan, Al-Kasasbeh, Malak M., Naffa, Randa G., Ismail, Mohammad A., Abdullah, Mohammed S., Ismail, Said I., Obeidat, Ma’en, Hernández Cordero, Ana I., Sin, Don D., Bossé, Yohan, Joubert, Philippe, Hao, Ke, Nickle, David, Timens, Wim, van den Berge, Maarten, Feng, Yen-Chen Anne, Mercader, Josep, Weiss, Scott T., Karlson, Elizabeth W., Smoller, Jordan W., Murphy, Shawn N., Meigs, James B., Woolley, Ann E., Green, Robert C., Mandla, Ravi, Schroeder, Philip, Perez, Emma F., Lee, Seung Hyuk T., Flores-Silva, Fernando Daniel, Chiquete, Erwin, Cantú-Brito, Carlos, Sifuentes-Osornio, José, de León-Garduño, Alfredo Ponce, Román-Montes, Carla Marina, Chávez-Manzanera, Emma, Velasco, Donaji Gómez, Martagón-Rosado, Alexandro, Cruz-Bautista, Ivette, Gómez-Pérez, Francisco Javier, Díaz-Olavarrieta, Claudia, Valdés, Paloma Almeda, Muñóz-Hernández, Linda Liliana, Mehta, Roopa Pravin, Elías-López, Daniel, Tusié-Luna, Teresa, Pajukanta, Päivi, Sukhatme, Mihir G., Moreno-Macías, Hortensia, Ruth, Johnson, González-Behn-Eschenburg, Sebastián, García-Grimshaw, Miguel, Guillen-Pineda, Luz Elizabeth, de los Ángeles Vargas-Martínez, María, Rodríguez, Maribel, Rodríguez-Guillén, Rosario, Ordoñez, María Luisa, Rajme-López, Sandra, González-Lara, María Fernanda, Luna-Moreno, Dalia, de Jesús Suárez López, Jannet, Guillén-Quintero, Daniela Mariel, Vega, Juan, Duran-Coyote, Salvador, Guerra-García, María Teresa, Durán-Gómez, Michelle, Vigueras-Hernández, Alma, Ramírez-Jiménez, Marco Eduardo, Grajeda-González, Samara Lissete, Ramos-Galicia, Enrique Manuel, Ramírez-Carrillo, Martha Fernanda, Fernandez-Ruiz, Juan, Chirino-Pérez, Amanda, Romero-Molina, Ángel Omar, Zavaleta, David Alejandro Fuentes, Jaramillo, María Andrea Mac Donald, López, Katia Jarely Prieto, Incontri-Abraham, Diego, Rosado, Wendy Natalia, Catalán, María Alonso, Aguilar, Sonia Evelyn Vital, Zamudio, Ileana Paola Montero, Ruíz-Ruíz, Eduardo, de Jesús Carrera García, Kevin, Guerrero, Cristina Villarreal, Martínez, Ana Isabel Rodríguez, Moscoso-Sánchez, Rogelio, del Consuelo Rodríguez Mancilla, María, Villa, Antonio, Luna-Ramírez, Samuel Alejandro, Hernández-Hernández, Sergio, Frias, Erika, Campos, Alejandro, Morales-Sosa, Paola Alessandra, Toxqui-Merchant, Luis Enrique, García, Karla, Pasaniuc, Bogdan, Butte, Manish J., Geschwind, Daniel H., Aguilar-Salinas, Carlos A., Heidecker, Bettina, Kurth, Florian, Sander, Leif E., Skurk, Carsten, Landmesser, Ulf, Karadeniz, Zehra, Wang, Xiaomin, Poller, Wolfgang, Suwalski, Phillip, Ripke, Stephan, Braun, Alice, Kraft, Julia, Mayer, Alena, Lippert, Lena J., Helbig, Elisa T., Thibeault, Charlotte, Awasthi, Swapnil, Mbarek, Hamdi, Saad, Chadi, Al-Sarraj, Yaser, Badji, Radja Messai, Al-Muftah, Wadha, Thani, Asma Al, Afifi, Nahla, Sadiq, Fouzia, Khan, Mohammad I., Bhutta, Muhammad J., Khan, Hania, Khan, Madeeha, Ain, Quratul, Junaid, Ayesha, Khan, Ejaz A., Sypniewski, Mateusz, Lejman, Adrian, Zawadzki, Paweł, Sztromwasser, Paweł, Król, Zbigniew, Dobosz, Paula, Stojak, Joanna, Flores, Carlos, Carracedo, Ángel, Aguilar, Carlos, Arranz, María J., Baptista-Rosas, Raúl C., Bezerra, Joao F., Bezerra, Marcos A. 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C., Pérez-Matute, Patricia, Perez, Patricia, Perucho, Teresa, Porras-Hurtado, Gloria L., Pujol, Aurora, Fernández-Rodríguez, Amanda, Jimenez-Sousa, María A., Rodríguez-Ruiz, Emilio, Rodriguez-Artalejo, Fernando, Rodriguez-Garcia, José A., Ruiz-Cabello, Francisco, Soria, José Manuel, Tamayo, Eduardo, Teper, Alejandro, Torres-Tobar, Lilian, Urioste, Miguel, Yáñez, Zuleima, Zarate, Ruth, Guillen-Navarro, Encarna, Ayuso, Carmen, González-Neira, Anna, Riancho, José A., Rojas-Martinez, Augusto, Lapunzina, Pablo, Cruz, Raquel, Diz-de Almeida, Silvia, Ceballos, Francisco C., Lorenzo-Salazar, José M., González-Montelongo, Rafaela, Quintela, Inés, Pita, Guillermo, Gago-Domínguez, Manuela, Porras, Marta Sevilla, Tenorio-Castaño, Jair Antonio, Nevado, Julian, Aguado, Jose María, Aguilera-Albesa, Sergio, Almadana, Virginia, Almoguera, Berta, Alvarez, Nuria, Andreu-Bernabeu, Álvaro, Arango, Celso, Artiga, Maria-Jesus, Barreda-Sánchez, María, Belhassen-Garcia, Moncef, Boix-Palop, Lucía, Brion, María, Carbonell, Cristina, Castelao, Jose E., Cortes-Sanchez, Jose L., Corton, Marta, Darnaude, M. 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H., Sækmose, Susanne G., Zeberg, Hugo, Nkambul, Lindo, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Tardif, Nicolas, Rooyackers, Olav, Grip, Jonathan, Maricic, Tomislav, Heid, Iris M., Wagner, Ralf, Überla, Klaus, Winkler, Thomas W., Wiegrebe, Simon, Gorski, Mathias, Stark, Klaus J., Peterhoff, David, Einhauser, Sebastian, Niller, Hans-Helmut, Beileke, Stephanie, Johnson, Ruth, Freimer, Nelson, Ding, Yi, Chiu, Alec, Chang, Timothy S., Boutros, Paul, Karczewski, Konrad J., Martin, Alicia R., Wilson, Daniel J., Spencer, Chris C. A., Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Atkinson, Elizabeth G., Tsuo, Kristin, Baya, Nikolas, Turley, Patrick, Gupta, Rahul, Walters, Raymond K., Palmer, Duncan S., Sarma, Gopal, Solomonson, Matthew, Cheng, Nathan, Lu, Wenhan, Churchhouse, Claire, Goldstein, Jacqueline I., King, Daniel, Zhou, Wei, Seed, Cotton, Daly, Mark J., Finucane, Hilary, Bryant, Sam, Satterstrom, F. 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C., Thompson, Wesley K., Fan, Chun Chieh, Johnson, Emma C., Niazyan, Lyudmila, Davidyants, Mher, Arakelyan, Arsen, Avetyan, Diana, Bekbossynova, Makhabbat, Tauekelova, Ainur, Tuleutayev, Mukhtar, Sailybayeva, Aliya, Ramankulov, Yerlan, Zholdybayeva, Elena, Dzharmukhanov, Jarkyn, Kassymbek, Kuat, Tsechoeva, Tatyana, Turebayeva, Gulsimzhan, Smagulova, Zauresh, Muratov, Timur, Khamitov, Sadyk, Kwong, Alex S. F., Timpson, Nicholas J., Niemi, Mari E. K., Rahmouni, Souad, Guntz, Julien, Beguin, Yves, Pigazzini, Sara, Nkambule, Lindokuhle, Georges, Michel, Moutschen, Michel, Misset, Benoit, Darcis, Gilles, Gofflot, Stéphanie, Bouysran, Youssef, Busson, Adeline, Peyrassol, Xavier, Wilkin, Françoise, Pichon, Bruno, Smits, Guillaume, Vandernoot, Isabelle, Goffard, Jean-Christophe, Tiembe, Nicky, Morrison, David R., Afilalo, Jonathan, Mooser, Vincent, Richards, J. 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T., Hung, Rayjean J., Lawless, Jerry F., Paterson, Andrew D., Sun, Lei, Rauh, Michael, Briollais, Laurent, Gingras, Anne-Claude, Bombard, Yvonne, Pugh, Trevor J., Simpson, Jared, Goneau, Lee W., Halevy, Anat R., Maslove, David M., Borgundvaag, Bjug, Devine, Luke, Bearss, Erin, Richardson, David, Arnoldo, Saranya, Friedman, Steven Marc, Taher, Ahmed, Stern, Seth, Dagher, Marc, Vasilevska-Ristovska, Jovanka, Biggs, Catherine M., Mickiewicz, Beata, Strug, Lisa J., Scherer, Stephen W., Aziz, Naveed, Jones, Steven J. M., Knoppers, Bartha M., Lathrop, Mark, Turvey, Stuart E., Yeung, Rae S. 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Muscatello, Antonio, Voza, Antonio, Rando-Segura, Ariadna, Solier, Aurora, Cortes, Beatriz, Mateos, Beatriz, Nafria-Jimenez, Beatriz, Schaefer, Benedikt, Bellinghausen, Carla, Ferrando, Carlos, de la Horra, Carmen, Quereda, Carmen, Scollo, Chiara, Lange, Christoph, Hu, Cinzia, Paccapelo, Cinzia, Angelini, Claudio, Cappadona, Claudio, Bianco, Cristiana, Cea, Cristina, Sancho, Cristina, Hoff, Dag Arne Lihaug, Galimberti, Daniela, Haschka, David, Jiménez, David, Pestaña, David, Toapanta, David, Muñiz-Diaz, Eduardo, Azzolini, Elena, Sandoval, Elena, Binatti, Eleonora, Scarpini, Elio, Casalone, Elisabetta, Urrechaga, Eloisa, Paraboschi, Elvezia Maria, Pontali, Emanuele, Reverter, Enric, Calderón, Enrique J., Navas, Enrique, Contro, Ernesto, Arana-Arri, Eunate, Aziz, Fátima, Sánchez, Félix García, Ceriotti, Ferruccio, Martinelli-Boneschi, Filippo, Peyvandi, Flora, Blasi, Francesco, Malvestiti, Francesco, Medrano, Francisco J., Mesonero, Francisco, Rodriguez-Frias, Francisco, Müller, Fredrik, 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Valsecchi, Maria G., Hernandez-Tejero, María, Vehreschild, Maria J. 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S., Elnagdy, Marwa H., Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T., El-Lawaty, Walaa M., Torky, Mohamed S., El-Shanshory, Mohamed R., Elzeiny, Ahmed, Rashad, Amal, Mansour, Tamer A., Yassen, Amr M., Hegazy, Mohamed A. F., Okasha, Kamal, Eid, Mohammed A., Hanteera, Moahmed S., Medina-Gomez, Carolina, Ikram, M. Arfan, Uitterlinden, Andre G., Ripatti, Samuli, Jermy, Bradley, Ruotsalainen, Sanni, Kristiansson, Kati, Koskelainen, Sami, Perola, Markus, Donner, Kati, Kivinen, Katja, Palotie, Aarno, Kaunisto, Mari, Julienne, Hanna, Aschard, Hugues, Deleuze, Jean-Francois, Debette, Stephanie, Tregouet, David-Alexandre, Abel, Laurent, Henches, Léo, Lefloch, Edith, Claire, Dandine-Roulland, Sakuntabhai, Anavaj, Bourgeron, Thomas, Olaso, Robert, Daian, Delphine Bacq, Pellegrin, Isabelle, Casanova, Jean-Laurent, Cobat, Aurélie, Jouanguy, Emmanuelle, Zhang, Qian, Ghosn, Jade, Mentré, France, Laouénan, Cédric, Tubiana, Sarah, Chirouze, Catherine, Quintana-Murci, Luis, Patin, Etienne, Duffy, Darragh, Boland, Anne, Carreras, Anna, Galván-Femenía, Iván, Farré, Xavier, Cortés, Beatriz, Mercader, Josep Maria, Guindo-Martinez, Marta, Torrents, David, Garcia-Aymerich, Judith, Castaño-Vinyals, Gemma, Dobaño, Carlota, van Heel, David A., Hunt, Karen A., Trembath, Richard C., Jacobs, Benjamin Meir, Huang, Qin Qin, Martin, Hilary C., Mason, Dan, Trivedi, Bhavi, Wright, John, Munisamy, Malathy, Finer, Sarah, Griffiths, Christopher J., McCarthy, Mark I., Rosenberger, Carrie, Lee, Jong Eun, Chang, Diana, Hammer, Christian, Hunkapiller, Julie, Mahajan, Anubha, Pendergrass, Rion, Sucheston-Campbell, Lara, Yaspan, Brian, Lee, Hyun Soo, Shin, Eunsoon, Jang, Hye Yoon, Kim, Sunmie, Kym, Sungmin, Kim, Yeon-Sook, Jeong, Hyeongseok, Kwon, Ki Tae, Kim, Shin-Woo, Kim, Jin Yong, Jang, Young Rock, Kim, Hyun ah, Lee, Ji yeon, Lee, Jeong Eun, Lee, Shinwon, Choe, Kang-Won, Kang, Yu Min, Jee, Sun Ha, Jung, Keum Ji, Park, Hyun-Young, Kim, Bong-Jo, Kim, Young Jin, Hwang, Mi Yeong, Yoon, Kyungheon, Pairo-Castineira, Erola, Rawlik, Konrad, Caulfield, Mark J., Baillie, J. Kenneth, Griffiths, Fiona, Bretherick, Andrew D., Stuckey, Alex, Odhams, Christopher A., Walker, Susan, Russell, Clark D., Malinauskas, Tomas, Wu, Yang, Shen, Xia, Elliott, Katherine S., Morrice, Kirstie, Keating, Sean, Wang, Bo, Rhodes, Daniel, Klaric, Lucija, Zechner, Marie, Parkinson, Nick, Fawkes, Angie, Murphy, Lee, Vitart, Veronique, Wilson, James F., Yang, Jian, Scott, Richard H., Moutsianas, Loukas, Law, Andy, Begg, Colin, Hendry, Sara Clohisey, Hinds, Charles, Horby, Peter, Knight, Julian, Ling, Lowell, Maslove, David, McAuley, Danny, Millar, Johnny, Montgomery, Hugh, Nichol, Alistair, Openshaw, Peter J. M., Ponting, Chris P., Rowan, Kathy, Semple, Malcolm G., Shankar-Hari, Manu, Summers, Charlotte, Walsh, Timothy, Pan, Jacqueline, Grau, Neus, Jones, Tim Owen, Lim, Rosario, Marotti, Martina, Whitton, Christopher, Bociek, Aneta, Campos, Sara, Arbane, Gill, Ostermann, Marlies, Cha, Mina, DAmato, Fabiola, Kosifidou, Eirini, Lorah, Shelley, Morera, Kyma, Brady, Laura, Hugill, Keith, Henning, Jeremy, Bonner, Stephen, Headlam, Evie, Jones, Jessica, List, Abigail, Morley, Joanne, Welford, Amy, Kamangu, Bobette, Ratnakumar, Anitha, Shoremekun, Abiola, Alldis, Zoe, Astin-Chamberlain, Raine, Bibi, Fatima, Biddle, Jack, Blow, Sarah, Bolton, Matthew, Borra, Catherine, Bowles, Ruth, Burton, Maudrian, Choudhury, Yasmin, Cox, Amber, Easthope, Amy, Ebano, Patrizia, Fotiadis, Stavros, Gurasashvili, Jana, Halls, Rosslyn, Hartridge, Pippa, Kallon, Delordson, Kassam, Jamila, Lancoma-Malcolm, Ivone, Matharu, Maninderpal, May, Peter, Mitchelmore, Oliver, Newman, Tabitha, Patel, Mital, Pheby, Jane, Pinzuti, Irene, Prime, Zoe, Prysyazhna, Oleksandra, Shiel, Julian, Taylor, Melanie, Tierney, Carey, Zongo, Olivier, Wood, Suzanne, Zak, Anne, Collier, David, Mundy, Manuela, Thompson, Christopher, Pritchard, Lisa, Gellamucho, Minnie, Cartlidge, David, Bandla, Nageswar, Bailey, Lucy, Davies, Michelle, Delaney, Jane, Scott, Leanne, Abdelrazik, Marwa, Alasdair, Frater, Carter, David, Elhassan, Munzir, Ganesan, Arunkumar, Jenkins, Samuel, Lamond, Zoe, Purohit, Dharam, Rohit, Kumar, Saleem, Malik, Wall, Alanna, Xavier, Kugan, Bakthavatsalam, Dhanalaksmi, Gehad, Kirolos, Gnanapragasam, Pakeerathan, Jain, Kapil, Jain, Swati, Malik, Abdul, Pappachan, Naveen, Moreno-Cuesta, Jeronimo, Haldeos, Anne, Vincent, Rachel, Oziegb, Maryjane, Cavazza, Anna, Cockrell, Maeve, Corcoran, Eleanor, Depante, Maria, Finney, Clare, Jerome, Ellen, Knighton, Abigail, Nayak, Monalisa, Pappa, Evita, Saha, Rohit, Saha, Sian, Dodd, Andrew, O’Reilly, Kevin, McPhail, Mark, Clarey, Emma, Noble, Harriet, Smith, John, Coghlan, Phoebe, Brett, Stephen, Gordon, Anthony, Templeton, Maie, Antcliffe, David, Banach, Dorota, Darnell, Sarah, Fernandez, Ziortza, Jepson, Eleanor, Mohammed, Amal, Rojo, Roceld, Arias, Sonia Sousa, Gurung, Anita Tamang, Wong, Jenny, Fernandez-Roman, Jaime, Hamilton, David O., Johnson, Emily, Johnston, Brian, Martinez, Maria Lopez, Mulla, Suleman, Waite, Alicia A. C., Williams, Karen, Waugh, Victoria, Welters, Ingeborg, Emblem, Jessica, Norris, Maria, Shaw, David, Bashyal, Archana, Beer, Sally, Hutton, Paula, McKechnie, Stuart, Davidson, Neil, Mathew, Soya, Readion, Grace, Ryu, Jung, Wilson, Jean, Agrawal, Shruti, Elston, Kay, Jones, Megan, Meaney, Eoghan, Polgarova, Petra, Elbehery, Muhammad, Daubney, Esther, Ng, Anthony, Marshall, Jocelyn, Pathan, Nazima, Stroud, Katerina, White, Deborah, Andrew, Angela, Ashraf, Saima, Clark, Amy, Dent, Martin, Langley, Margaret, Peters, Cecilia, Ryan, Lucy, Sampson, Julia, Wei, Shuying, Baddeley, Alice, Meredith, Megan, Morris, Lucy, Gibbons, Alexandra, McLoughlin, Lisa, Delgado, Carlos Castro, Clark, Victoria, Dawson, Deborah, Ding, Lijun, Durrant, Georgia, Ezeobu, Obiageri, Harrison, Abiola, Hurt, William James, Kanu, Rebecca, Kinch, Ashley, Leaver, Susannah, Lisboa, Ana, Mathew, Jisha, Patel, Kamal, Saluzzio, Romina Pepermans, Rawlins, John, Samakomva, Tinashe, Shah, Nirav, Sicat, Christine, Texeira, Joana, Queiroz, Joana Gomes De, Gloria, Edna Fernandes Da, Maccacari, Elena, Yun, Nikki, Manna, Soumendu, Farnell-Ward, Sarah, Maizcordoba, Maria, Thanasi, Maria, Ali, Hawakin Haji, Hastings, Janice, Grauslyte, Lina, Hussain, Musarat, Ruge, Bobby, King, Sam, Pogreban, Tatiana, Rosaroso, Lace, Smith, Helen, Phull, Mandeep-Kaur, Adams, Nikkita, Franke, George, George, Aparna, Salciute, Erika, Wong, Joanna, Dunne, Karen, Flower, Luke, Sharland, Emma, Sra, Sukhmani, Andrew, Gillian, Callaghan, Marie, Barclay, Lucy, Marshall, Lucy, Amamio, Maria, Birch, Sophie, Briton, Kate, Clark, Sarah, Doverman, Katerine, Hope, Dave, Mcculloch, Corrienne, Simpson, Scott, Singleton, Jo, Fernandez, Rita, Allen, Meryem, Baptista, David, Crowe, Rebecca, Fox, Jonathan, Khera, Jacyntha, Loveridge, Adam, McKenley, India, Morino, Eriko, Naranjo, Andres, O’Connor, Denise, Simms, Richard, Sollesta, Kathryn, Swain, Andrew, Venkatesh, Harish, Herdman-Grant, Rosie, Joseph, Anna, Nown, Angela, Rose, Steve, Pogson, David, Boxall, Helen, Brimfield, Lutece, Claridge, Helen, Daly, Zoe, George, Shenu, Gribbin, Andrew, Cheema, Yusuf, Cutler, Sean, Richards, Owen, Roynon-Reed, Anna, Cherian, Shiney, Heron, Anne Emma, Williams, Gemma, Szakmany, Tamas, Waters, Abby, Collins, Kim, Dunhill, Jill, Jones, Ffion, Morris, Rebecca, Ship, Lucy, Cardwell, Amy, Ali, Syamlan, Bhatterjee, Ravi, Bolton, Rachel, Chukkambotla, Srikanth, Coleman, Dabheoc, Dalziel, Jack, Dykes, Joseph, Fine, Christopher, Gay, Bethan, Goddard, Wendy, Goodchild, Drew, Harling, Rhiannan, Hijazi, Muhammad, Keith, Sarah, Khan, Meherunnisa, Matt, Roseanna, Ryan-Smith, Janet, Saad, Samuel, Springle, Philippa, Thomas, Jacqueline, Truman, Nick, Kazi, Aayesha, Smith, Matthew, Collier, Heather, Davison, Chloe, Duberley, Stephen, Hargreaves, Jeanette, Hartley, Janice, Patel, Tahera, Smith, Ellen, Kent, Alissa, Goodwin, Emma, Zaki, Ahmed, Tibke, Clare, Hopkins, Susan, Gerrard, Hywel, Jackson, Matthew, Bennett, Sara, Marsh, Liane, Mills, Rebecca, Bell, Jessica, Campbell, Helen, Dawson, Angela, Dodds, Steve, Duffy, Stacey, Gallagher, Lisa, McCafferty, Gemma, Short, Stacey, Smith, Tracy, Thomas, Kirsty, Walker, Claire, Reynolds, Jessica, Yates, Bryan, McKie, Hayley, Panteli, Maria, Thompson, Maria, Waddell, Gail, Beger, Sarah De, Abraheem, Azmerelda, Dunmore, Charlie, Girach, Rumanah, Jones, Rhianna, London, Emily, Nagra, Imrun, Nasir, Farah, Sainsbury, Hannah, Smedley, Clare, Brearey, Stephen, Burchett, Caroline, Cawley, Kathryn, Faulkner, Maria, Jeffrey, Helen, Bamford, Peter, Shaikh, Firdaus, Slack, Lauren, Davies, Angela, Brooke, Hollie, Suarez, Jose Cebrian, Charlesworth, Ruth, Hansson, Karen, Norris, John, Poole, Alice, Sandhu, Rajdeep, Smithson, Elizabeth, Thirumaran, Muthu, Wagstaff, Veronica, Buckley, Sarah, Sloan, Brendan, Rose, Alastair, Major, Amy, Metcalfe, Alexandra, Almaden-Boyle, Christine, Austin, Pauline, Chapman, Susan, Eros, Alexandre, Cabrelli, Louise, Cole, Stephen, Whyte, Clare, Casey, Matt, Bafitis, Vasileios, Tsinaslanidis, George, George, Cassandra, Khade, Reena, Black, Christopher, Ashok, Sundar Raj, Farley, Sean, Brinkworth, Elaine, Harford, Rachel, Murphy, Carl, Williams, Marie, Newey, Luke, Toghill, Hannah, Lewis, Sophie, Rees, Tabitha, Battle, Ceri, Baker, Mark, Travers, Jenny, Chesters, Karen, Baxter, Nicola, Arnott, Andrew, McCreath, Gordan, McParland, Christopher, Rooney, Laura, Sim, Malcolm, Henderson, Steven, Abel, Lynn, Dalton, Carol, Kennedy-Hay, Sophie, O’Donohoe, Lynn, O’Hare, Megan, Orlikowska, Izabela, Parker, Natasha, McNeela, Fiona, Lyle, Amanda, Hughes, Alistair, Radhakrishnan, Jayachandran, Gibson, Sian, Bancroft, Hollie, Bellamy, Mary, Daglish, Jacqueline, Kadiri, Salma, Moore, Faye, Rhodes, Joanne, Sangombe, Mirriam, Peterkin, Zhane, Scriven, James, Carmody, Margaret, Cottle, Juliet, Peasgood, Emily, de Gordoa, Laura Ortiz-Ruiz, Phillips, Claire, Skinner, Denise, Cinquina, Zoe, Howard, Kate, Joy, Rosie, Roche, Samantha, Birkinshaw, Isobel, Carter, Joseph, Ingham, Jo, Marshall, Nicola, Pearson, Harriet, Scott, Zoe, Dasgin, Jo, Gill, Jaspret, Nilsson, Annette, Bamford, Amy, Hull, Diana, Ahmadhaider, Nafeesah, Bates, Michelle, McGhee, Christopher, Ellis, Hannah, Howe, Gwenllian Sera, Singh, Jayaprakash, Stroud, Natalie, Roche, Lisa, Lynch, Ceri, Deacon, Bethan, Pothecary, Carla, Smeaton, Justyna, Agravante, Kevin, Krishnamurthy, Vinodh, Diaba, Cynthia, John, Lincy, Lim, Lai, Jha, Rajeev, Egan, Jasmine, Felton, Timothy, Glasgow, Susannah, Padden, Grace, Choudhr, Ozerah, Bradley-Potts, Joanne, Moss, Stuart, Lingeswaran, Saejohn, Alexander, Peter, Brandwood, Craig, Fiouni, Sofia, Ward, Luke, Allen, Schvearn, Shaw, Jane, Smith, Christopher, Adanini, Oluronke, Collins, Rebecca, Msiska, Maines, Ofori, Linda, Bhatia, Nikhil, Dolan, Hayley, Brunton, Mark, Caterson, Jess, Coles, Holly, Keating, Liza, Tilney, Emma, Jacques, Nicola, Frise, Matthew, Armistead, Jennifer, Bartley, Shauna, Bhuie, Parminder, Rai, Sabi, Tomkova, Gabriela, Greer, Sandra, Shuker, Karen, Tridente, Ascanio, Dobson, Emma, Hunt, Jodie, Tully, Redmond, Dearden, Joy, Drummond, Andrew, Kamath, Prakash, Bullock, Emily, Mulcahy, Michelle, Munt, Shelia, O’Connor, Grainne, Philbin, Jennifer, Rishton, Chloe, Scott, Chloe, Winnard, Sarah, Hasni, Nurkamalia, Gascoyne, Rachel, Hawes, Joanne, Pritchard, Kelly, Stevenson, Lesley, Whileman, Amanda, Beavis, Sarah, Bishop, Lauren, Cart, Cindy, Dale, Katie, Kelly-Baxter, Mary, Mendelski, Adam, Moakes, Emma, Smith, Rheanna, Woodward, Jan, Wright, Stephanie, Allan, Angela, Botello, Adriana, Liew, Jade, Medhora, Jasmine, Trumper, Erin, Savage, Felicity, Scott, Teresa, Place, Marc, Kaye, Callum, Benyon, Sarah, Marriott, Suzie, Park, Linda, Quinn, Helen, Skyes, Daisy, Zitter, Lily, Baines, Kizzy, Gordon, Elizabeth, Keenan, Samantha, Pitt, Andrew, Duffy, Katharine, Ireland, Jane, Semple, Gary, Turner, Lynne, Cathcart, Susanne, Rimmer, Dominic, Puxty, Alex, Puxty, Kathryn, Hurst, Andrew, Miller, Jennifer, Speirs, Susan, Walker, Lauren, Bradshaw, Zena, Brown, Joanna, Melling, Sarah, Preston, Stephen, Slawson, Nicola, Warden, Scott, Beasley, Alanna, Stoddard, Emma, Benham, Leonie, Cupitt, Jason, Caswell, Melanie, Elawamy, Lisa, Wignall, Ashleigh, Roberts, Belinda, Golding, Hannah, Leggett, Samantha, Male, Michelle, Marani, Martyna, Prager, Kirsty, Williams, Toran, Golder, Kim, Jones, Oliver, Cusack, Rebecca, Bolger, Clare, Burnish, Rachel, Carter, Michael, Jackson, Susan, Salmon, Karen, Biss, Jonathan, Aquino, Maia, Croft, Maria, Frost, Victoria, White, Ian, Govender, Keshnie, Webb, Natasha, Stapleton, Liana, Wells, Colin, Nikitas, Nikitas, Sanchez - Rodriguez, Ana, Spencer, Kayleigh, Stowe, Bethan, Izzard, Yvonne, Poole, Michelle, Monnery, Sonja, Trotman, Sallyanne, Beech, Valerie, Combes, Edward, Joefield, Teishel, Covernton, Patrick, Savage, Sarah, Woodward, Elizabeth, Camsooksai, Julie, Reschreiter, Henrik, Barclay, Charlotte, DeAth, Yasmin, Dube, Judith, Humphrey, Charlotte, Jenkins, Sarah, Langridge, Emma, Milne, Rebecca, Wadams, Beverley, Woolcock, Megan, Brett, Michael, Digby, Brian, Gemmell, Lisa, Hornsby, James, MacGoey, Patrick, O’Neil, Pauline, Price, Richard, Sundaram, Radha, Rodden, Natalie, Thomson, Nicola, Rooney, Kevin, Currie, Susan, Henderson, Philip, Ogg, Bethan, Whiteley, Simon, Wilby, Liz, Long, Kate, Matthew, Shailamma, Salada, Sheila, Trott, Susan, Watts, Sarah, Friar, Zoe, Speight, Abigail, Bastion, Victoria, Chandna, Humza, Djeugam, Brice, Haseeb, Muhammad, Kent, Harriet, Lubimbi, Gamu, Murdoch, Sophie, Thomas, Alastair, David, Beena, Lorusso, Rachel, Vochin, Ana, Penacerrada, Melchizedek, Wulandari, Retno, Heath, Charlotte, Jakkula, Srinivas, Morris, Anna, Ahmed, Ashar, Nune, Arvind, Buttriss, Claire, Whitaker, Emma, Davey, Miriam, Golden, David, Acklery, Amy, Fernandes, Fabio, Seaman, Bec, Earl, Victoria, Collins, Amy, Khaliq, Waqas, Adam, Rachel, Treus, Estefania, Holland, Sarah, Alfonso, Jordan, Blackledge, Bethan, Bruce, Michelle, Durrans, Laura Jayne, Eltayeb, Ayaa, Harris, Jade, Hey, Samuel, Hruska, Martin, Lamb, Thomas, Rothwell, Joanne, Fitzgerald, Adele, Lindergard, Gabriella, T-Michael, Helen, Duncan, Tracey, Baxter-Dore, Sharon, Cooper, Lisa, Fox, Claire, Guerin, Jacinta, Hodgkiss, Tracey, Connolly, Karen, McAlinden, Paul, Bridgett, Victoria, Fearby, Maggie, Gulati, A., Hanson, Helen, Kelly, Sinead, McCormack, Louise, Nixon, Rachel, Robinson, Philip, Slater, Victoria, Stephenson, Elaine, Webster, Andrea, Webster, K., Hays, Carole, Hudson, Anne, Patel, Bijal, Clement, Ian, Davis, John, Francis, Sarah, Jerry, Douglas, Abernathy, Caroline, Foster, Louise, Gratrix, Andrew, Cabral-Ortega, Llucia, Hines, Matthew, Martinson, Victoria, Stones, Elizabeth, Winter, Karen, Barrow, Esther, Wylie, Katharine, Baines, Deborah, Birchall, Katie, Kolakaluri, Laurel, Clark, Richard, Sukumaran, Anila, Barker, Melanie, Paripoorani, Deborah, Smith, Lara, Taylor, Charlotte, Downes, Charlotte, Hayman, Melanie, Riches, Katie, Daniel, Priya, Subramanian, Deepak, Holding, Kathleen, Hilton, Mary, Mcdonald, Carly, Richardson, Georgina, Halladay, Georgia, Harding, Peter, Reddy, Amie, Turner-Bone, Ian, Wilding, Laura, Parker, Robert, Lloyd, Michaela, Smith, Leanne, Kelly, Charlie, Lazo, Maria, Neal, Alan, Walton, Olivia, Melville, Julie, Naisbitt, Jay, Joseph, Rosane, Callam, Sara, Hudig, Lisa, Keshet-Price, Jocelyn, Stammers, Katie, Convery, Karen, Randell, Georgina, Fottrell-gould, Deirdre, Mwaura, Esther, Sutherland, Sara-Beth, Stewart, Richard, Mew, Louise, Wren, Lynn, Thrasyvoulou, Laura, Willis, Heather, Hopkins, Bridget, Lenton, Daniel, Roberts, Abigail, Bokhari, Maria, Lucas, Rachael, McCormick, Wendy, Ritzema, Jenny, Linnett, Vanessa, Sanderson, Amanda, Wild, Helen, Flanagan, Rebecca, Hull, Robert, Rhead, Kat, McKenna, Emma, Hughes, Gareth, Anderson, Jennifer, Jones, Kelly, Latham, Scott, Riley, Heather, Coulding, Martina, Clark, Martyn, McCormick, Jacqueline, Mercer, Oliver, Potla, Darsh, Rehman, Hafiz, Savill, Heather, Turner, Victoria, Jude, Edward, Kilroy, Susan, Apetri, Elena, Basikolo, Cathrine, Catlow, Laura, Collis, Matthew, Doonan, Reece, Harvey, Alice, Knowles, Karen, Lee, Stephanie, Lomas, Diane, Lyons, Chloe, McMorrow, Liam, Michael, Angiy, Pendlebury, Jessica, Perez, Jane, Poulaka, Maria, Proudfoot, Nicola, Slevin, Kathryn, Thomas, Vicky, Walker, Danielle, Dark, Paul, Charles, Bethan, McLaughlan, Danielle, Slaughter, Melanie, Horner, Dan, Marsden, Tracy, Andrews, Joyann, Beech, Emily, Akinkugbe, Olugbenga, Bamford, Alasdair, Belfield, Holly, Jones, Gareth A. L., McHugh, Tara, Meghari, Hamza, Ray, Samiran, Tomas, Ana Luisa, O’Neill, Lauran, Peters, Mark, Bell, Michael, Benkenstein, Sarah, Chisholm, Catherine, Davies, Charlene, Kupiec, Klaudia, Payne, Caroline, Halls, Joanna, Blakemore, Hayley, Goff, Elizabeth, Hayes, Kati, Smith, Kerry, Stephens, Deanna, Worner, Ruth, Borislavova, Borislava, Faulkner, Beverley, Thomas, Matt, Cookson, Ruth, Gendall, Emma, Larman, Georgina, Pope, Rebecca, Smalira, Artur, Priestley, Victoria, Cosier, Tracey, Millen, Gemma, Rand, James, Schumacher, Natasha, Sandhar, Roxana, Weston, Heather, Richardson, Neil, Cooper, Lucy, Jones, Cathy, Huang, Ya-Wen Jessica, Jacob, Reni, Denmade, Craig, Mcintyre, Lewis, Trodd, Dawn, Martin, Jane, Watson, Geoff, Bevan, Emily, Wreybrown, Caroline, Bano, Shereen, Bellwood, Ruth, Bentley, Michael, Bromley, Matt, Gurr, Lucy, Ledgard, Camilla, McGowan, Janet, Pye, Kate, Sellick, Kirsten, Stacey, Amelia, Warren, Deborah, Wilkinson, Brian, Akeroyd, Louise, Shafique, Huma, Morgan, James, Shorter, Susan, Swinger, Rachel, Waters, Emily, Lawton, Tom, Allan, Elizabeth, Darlington, Kate, Davies, Ffyon, Davies, Llinos, Easton, Jack, Kumar, Sumit, Lean, Richard, Mackay, Callum, Pugh, Richard, Qiu, Xinyi, Rees, Stephanie, Scanlon, Jeremy, Lewis, Joanne, Menzies, Daniel, Bolger, Annette, Davies, Gwyneth, Davies, Jennifer, Garrod, Esther, Jones, Helen, Manley, Rachel, Williams, Hannah, Frankham, Jordan, Pitts, Sally, White, Nigel, Branney, Debbie, Tiller, Heather, Efford, Georgia, Garland, Zoe, Grimmer, Lisa, Gumbrill, Bethany, Johnson, Rebekah, Sweet, Katie, Bewley, Jeremy, Coleman, Christina, Corcoran, Katie, Morano, Eva Maria Hernandez, Shiel, Rachel, Webster, Denise, Bonnici, Josephine, Daniel, Eleanor, Dell, Abbie, Kent, Melanie, Wilkinson, Ami, Brown, Ellen, Kay, Andrea, Campbell, Suzanne, Cowton, Amanda, Birt, Mark, Greenaway, Vicki, Potts, Kathryn, Hutton, Clare, Shepperson, Andrew, Forsey, Miranda, Nicholson, Alice, Vertue, Mark, Riches, Joanne, Kaliappan, Agilan, Nicholson, Anne, MacCallum, Niall, Raith, Eamon, Bercades, Georgia, Hass, Ingrid, Brealey, David, Martir, Gladys, Reyes, Anna, Smyth, Deborah, Zapatamartinez, Maria, Alvaro, Ana, Jetha, Champa, Ma, Louise, Booker, Lauren, Mostoles, Loreta, Pratley, Anezka, Altabaibeh, Abdelhakim, Parmar, Chetan, Gilbert, Kayleigh, Ferguson, Susie, Shepherd, Amy, Morris, Sheila, Baruah, Rosie, Lloyd, Georgina, Bell, Stephanie, Rivers, Vanessa, Purewal, Bally, Hammerton, Kate, Anderson, Susan, Birch, Janine, Collins, Emma, Oleary, Ryan, Cornell, Sarah, Jarmain, Jordan, Rogerson, Kimberley, Wakinshaw, Fiona, Woods, Lindsey, Rostron, Anthony, Elcioglu, Zeynep, Roy, Alistair, Bell, Gillian, Dickson, Holly, Wilcox, Louise, Katary, Amro, English, Katy, Hutter, Joanne, Pawley, Corinne, Doble, Patricia, Shovelton, Charmaine, Vaida, Marius, Purnell, Rebecca, Thomas, Ashly, Cagova, Lenka, Fofano, Adama, Holcombe, Helen, Mitchell, Alice Michael, Mwaura, Lucy, Praman, KrithivasanÂ, Garnr, Lucie, Mepham, Sue, Paques, Kitty, Vuylsteke, Alain, Mackie, Jennifer, Pearn, Carmen, Zamikula, Julie, Nyirenda, Maggie, Capozzi, Lisa, Reece-Anthony, Rosie, Noor, Hazma, Nilo, Alfa Cresia, Grove, Michelle, Daniel, Amelia, Finn, Joanne, White, Nikki, Saha, Rajnish, Badal, Bibi, Ixer, Karen, Duffin, Donna, Player, Ben, Hill, Helen, Cole, Jade, Brooks, Jenny, Davies, Rhys, Hunt, Lauren, Thomas, Emma, Williams, Angharad, Oblak, Metod, Thankachen, Mini, Irisari, Jamie, Sayan, Amrinder, Popescu, Monica, Finch, Cheryl, Jamieson, Andrew, Quinn, Alison, Cooper, Joshua, Liderth, Sarah, Waddington, Natalia, Burn, Iona, Manso, Katarina, Penn, Ruth, Tebbutt, Julie, Thornton, Danielle, Winchester, James, Hambrook, Geraldine, Shanmugasundaram, Pradeep, Craig, Jayne, Simpson, Kerry, Higham, Andrew, Sibbett, Louise, Paine, Sheila, Reed, Annabel, Conyngham, Jo-Anna, Mupudzi, Mcdonald, Thomas, Rachel, Wright, Mary, Griffin, Denise, Partridge, Richard, Corral, Maria Alvarez, Muchenje, Nycola, Sitonik, Mildred, Butler, Aaron, Folkes, Linda, Fox, Heather, Gardner, Amy, Helm, David, Hobden, Gillian, King, Kirsten, Margalef, Jordi, Margarson, Michael, Martindale, Tim, Meadows, Emma, Raynard, Dana, Thirlwall, Yvette, Baird, Yolanda, Gomez, Raquel, Martin, Darren, Hodgson, Luke, Corin, Clinton, Sidall, Erikka, Szabo, Densie, Floyd, Sharon, Davies, Hannah, Austin, Karen, Kelsall, Olivia, Wood, Hannah, Cornell, Thomas, Ralph, Kate, Bean, Sarah, Burt, Karen, Spivey, Michael, Richards, Carol, Tedstone, Rachel, Carmody, Siobhain, Zhao, Xiaobei, Page, Valerie, Guanco, Mark Louie, Hoxha, Elvira, Zorloni, Camilla, Dean, Charlotte, Jones, Emma, Carter, Emma, Dunn, Joshua, Kong, Thomas, Mahenthran, Mervin, Marsh, Chris, Holland, Maureen, Keenan, Natalie, Mahmoud, Mohamed, Lyons, Marc, Wassall, Helen, Young, Meghan, Bradley, Paul, Burda, Dorota, Donlon, Sinead, Harden, Lesley, Harris, Celia, Mayangao, Irving, Montaser, Rugia, Mtuwa, Sheila, Piercy, Charles, Smith, Eleanor, Stone, Sarah, Verula, Jerik, Blackman, Helen, Marriott, Cheryl, Michalak, Natalia, Creagh-Brown, Ben, Salberg, Armorel, Boyer, Naomi, Pristopan, Veronika, Maynard, Victoria, Walker, Rachel, Hormis, Anil, Collier, Dawn, Graham, Cheryl, McCormick, Jake, Warrington, Jake, Cosgrove, Denise, McFarland, Denise, Ratcliffe, Judith, Charnock, Rob, Wynter, Inez, Gill, Mandy, Kirk, Jill, Paul, Paul, Ratnam, Valli, Shelton, Sarah, Jardine, Catherine, Hay, Alasdair, Williams, Dewi, Durga, Latha, Hibbert, Meg, Kennard-Holden, Gareth, Woodford, Chrsitopher, Tetla, Dariusz, Price, Alicia, Thomas, Alice, Thorpe, Chris, Knights, Ellen, Ward, Donna, Laha, Shondipon, Verlander, Mark, Williams, Alexandra, Prout, Rachel, Langton, Helen, Watters, Malcolm, Hunt, Charlotte, Novis, Catherine, Arif, Sarwat, Cunningham, Amy, Hewitt, Claire, Hindale, Julia, Jackson-Lawrence, Karen, Shepardson, Sarah, Wills, Maryanne, Butler, Susie, Tavares, Silivia, Barber, Russell, Hilldrith, Annette, Hubbard, Kelly, Egginton, Dawn, Clark, Michele, Purvis, Sarah, Sinclair, Simon, Collins, Vicky, Landeg, Bethan, Sell, Craig, Coetzee, Samantha, Gales, Alistair, Otahal, Igor, Icke, Becky, Raj, Meena, Williams, Caroline, Williams, Jill, Hill, Lucy, Kayani, Abdul, Masunda, Bridgett, Gondo, Prisca, Atayeva, Nigara, Cruz, Carina, Pattison, Natalie, Burnett, Caroline, Hatton, Jonathan, Heeney, Elaine, Newton, Maria, Al-Moasseb, Hassan, Behan, Teresa, Player, Jasmine, Stead, Rachael, Mitra, Atideb, Nauyokas, Kirsty, Humphreys, Sally, Cockerill, Helen, Tampsett, Ruth, Postovalova, Evgeniya, Coventry, Tina, McGregor, Amanda, Fowler, Susan, Macmahon, Mike, Cochrane, Patricia, Pirie, Sandra, Hanley, Sarah, Ali, Asifa, Brady, Megan, Dale, Sam, Dance, Annalisa, Gledhill, Lisa, Greig, Jill, Hanson, Kathryn, Holdroyd, Kelly, Home, Marie, Ishaq, Tahira, Kelly, Diane, Matapure, Lear, Melia, Deborah, Mellor, Samantha, Merwaha, Ekta, Nortcliffe, Tonicha, Shaw, Lisa, Shaw, Ryan, Wood, Tracy, Bayo, Lee-Ann, Usher, Miranda, Wilson, Alison, Kitson, Ross, Pinnell, Jez, Robinson, Matthew, Boltwood, Kaitlin, Birch, Jenny, Bough, Laura, Tutton, Rebecca, Winter-Goodwin, Barbara, Goodsell, Josie, Taylor, Kate, Williams, Patricia, Williams, Sarah, Cave, Ashleigh, Rees, James, Imeson-Wood, Janet, Smith, Jacqueline, Amin, Vishal, Karthik, Komala, Kausar, Rizwana, Anastasescu, Elena, Reid, Karen, Anumakonda, Vikram, Stoddart, Ella, Demetriou, Carrie, Eckbad, Charlotte, Howie, Lucy, Mitchard, Sarah, Ramos, Lidia, White, Katie, Hierons, Sarah, Kelly, Fiona, Serrano-Ruiz, Alfredo, Evans, Gabrielle, Nicol, Liz, Wilkins, Joy, Hulacka, Kim, Debreceni, Gabor, Brown, Alison, Crickmore, Vikki, Hill, Kay, Kannan, Thogulava, Dagutao, Zenaida, Beesley, Kate, Lewis, Alison, Perry, Jess, Antony, Sherly, Board, Sarah, Buckley, Clare, Pippard, Lucy, Tanate, Alfonso, Wood, Diane, Kubisz-Pudelko, Agnieska, Gouda, Ayman, Auld, Fiona, Donnachie, Joanne, Murdoch, Euan, Prentice, Lynn, Runciman, Nikole, Senaratne, Dhaneesha, Short, Abigail, Sweeney, Laura, Symon, Lesley, Todd, Anne, Turner, Patricia, McCann, Erin, Salutous, Dario, Edmond, Ian, Whitelaw, Lesley, Bland, Yvonne, Kajtor, Istvan, Kavanagh, Lisa, Singler, Karen, Linfield-Brown, George, Moore, Luke Stephen Prockter, Vizcaychipi, Marcela, Martins, Laura, Moore, Luke, Bull, Rhian, Carungcong, Jaime, Allen, Louise, Beranova, Eva, Knight, Alicia, Price, Carly, Tilbey, Sorrell, Turney, Sharon, Hazelton, Tracy, Tutt, Gabriella, Arora, Mansi, Turki, Salah, Sinfield, Emily, Deery, Joanne, Ramos, Hazel, Cristiano, Daniele, Dormand, Natalie, Farzad, Zohreh, Gummadi, Mahitha, Salmi, Sara, Sloane, Geraldine, Varghese, Mathew, Thwaites, Vicky, Patel, Brijesh, Kamal, Liyanage, Zborowski, Anelise Catelan, Coe, Ryan, Anderson, Madeleine, Beadle, Jane, Coates, Charlotte, Collins, Katy, Crowley, Maria, Johnson, Laura, King, Laura, Paramsothy, Remi, Sargeant, Janet, Silva, Pedro, Stuart, Carmel, Taylor, June, Tyl, David, Wakefield, Phillipa, Kamundi, Charlotte, Olufuwa, Olumide, Belagodu, Zakaulla, Gherman, Anca, Oakley, Naomi, Allan, John, Geary, Tim, Meikle, Alistair, O’Brien, Peter, Wood, Stephen, Clark, Andrew, Houston, Gordon, Black, Karen, Clarkson, Michelle, D’Sylva, Stuart, Morrison, Alan, Norman, Kathryn, Taylor, Margaret, Clements, Suzanne, Cohrane, Catriona, Gonzalez, Nora, Strachan, Dominic, Beith, Claire, Moar, Kirsten, Anderson, Peter, Archer, Katie, Burtenshaw, Andrew, Clayton, Sarah, Cother, Naiara, Cowley, Nicholas, Davis, Caroline, Digby, Stephen, Durie, Alison, Harrison, Alison, Low, Emma, McAlindon, Michael, McCurdy, Alex, Morgan, Aled, Rankin, Tobias, Thrush, Jessica, Tranter, Helen, Vigurs, Charlie, Wild, Laura, Murphy, Lorna, Smythe, Michelle, Brickell, Kathy, Ali, Inthakab Ali Mohamed, Beaumont, Karen, Elsaadany, Mohamed, Fernandes, Kay, Ally, Sameena Mohamed, Rangarajan, Harini, Sarathy, Varun, Selvanayagam, Sivarupan, Vedage, Dave, White, Matthew, Coton, Zoe, Joshy, Aricsa, Blunt, Mark, Curgenven, Hollie, Botfield, Liam, Dexter, Catherine, Kuravi, Aditya, Butler, Joanne, Chadwick, Robert, Ranga, Poonam, Richardson, Lisa, Virgilio, Emma, Anwer, Maddiha, Garg, Atul, Botfield, Donna, Marriott, Xana, Stewart, Keely, Mullan, Dee, Gaylard, Jane, Nowak, Justyna, Jones, Sian, Crawley, Rikki, Crew, Abigail, Cunningham, Mishell, Daniels, Allison, Harrison, Laura, Hope, Susan, Lancaster, Nicola, Matthews, Jamie, Wray, Gemma, Inweregbu, Ken, Cutts, Sarah, Miller, Katharine, Brady, Ailbhe, Chan, Rebekah, McIvor, Shane, Prady, Helena, Mathew, Bijoy, Little, Jeff, Furniss, Tim, Wright, Chris, King, Bernadette, Wasson, Christopher, O’Neill, Aisling, Turley, Christine, McGuigan, Peter, Collins, Erin, Finn, Stephanie, Green, Jackie, McAuley, Julie, Nair, Abitha, Quinn, Charlotte, Tauro, Suzanne, Ward, Kathryn, McGinlay, Michael, Reddy, Kiran, Ahmad, Norfaizan, Anderson, Samantha, Barker, Joann, Bauchmuller, Kris, Birchall, Kathryn, Bird, Sarah, Cawthron, Kay, Chetam, Luke, Cole, Joby, Donne, Ben, Foote, David, Ford, Amber, Hanratty, Helena, Harrington, Kate, Hesseldon, Lisa, Housley, Kay, Jackson, Yvonne, Jarman, Claire, Kibutu, Faith, Lenagh, Becky, Macharia, Irene, Masuko, Shamiso, Milner, Leanne, Newell, Helen, Nwafor, Lorenza, Oxspring, Simon, Phillips, Patrick, Raithatha, Ajay, Rowland-Jones, Sarah, Smith, Jacqui, Thompson, Roger, Trower, Helen, Walker, Sara, Watson, James, Wiles, Matthew, Lye, Alison, Willson, Jayne, Mills, Gary, Harris, Sansha, Hartill, Eleanor, Barron, Anthony, Collins, Ciara, Kaul, Sundeep, Nolan, Claire, Polgar, Oliver, Prendergast, Claire, Rogers, Paula, Shokkar, Rajvinder, Woodruff, Meriel, Mahay, Kanta, Reed, Anna, Meyrick, Hayley, Passmore, Heather, Farwell, James, O’Connell, Susan, Gregory, Jane, Barberis, Luigi, Harper, Rosemary, Smith, Tim, Armstrong, Diane, Bowey, Angie, Cowley, Anne, Corner, Andrew, Highgate, Judith, Rutherfurd, Claire, Taylor, Jo-Anne, Goodwin, Sarah, Eapen, Beena, Trim, Fiona, Donnison, Phil, Armstrong, Lisa, Bates, Hayley, Dooks, Emma, Farquhar, Fiona, Kitching, Amy, McParland, Chantal, Packham, Sophie, Hairsine, Brigid, Andreou, Premetie, Hales, Dawn, Mathews, Megha, Patel, Rekha, Barry, Peter, Flint, Neil, Hailstone, Jessica, Ghuman, Navneet, Leonard, Bethany, Lees, Rachel, Butcher, Deborah, Leng, Katy, Butterworth-Cowin, Nicola, O’Sullivan, Susie, Ghosh, Alison, Williams, Emma, Adams, Colene, Agasou, Anita, Arden, Tracie, Beekes, Mandy, Bowes, Amy, Boyle, Pauline, Button, Heather, Carnahan, Mandy, Carter, Anne, Childs, Danielle, Hurford, Fran, Hussain, Yasmin, Javaid, Ayesha, Jones, James, Leigh, Michael, Martin, Terry, Millward, Helen, Motherwell, Nichola, Newman, Julie, Rikunenko, Rachel, Stickley, Jo, Summers, Julie, Ting, Louise, Tivenan, Helen, Donaldson, Denise, Capps, Nigel, Cale, Emily, Jose, Sanal, Osbourne, Wendy, Pajak, Susie, Rankin, Jayne, Tonks, Louise, Baird, Tracy, Harkins, Margaret, Ruddy, Jim, West, Joe, Duffield, Joseph, Mallon, Lewis, Smith, Oliver, Smuts, Sara, Campbell, Andy, Davies, Cate, Davies, Sarah, Hughes, Rachel, Jobes, Lisa, Whitehead, Victoria, Watkins, Clare, Bowman, Fiona, Milligan, Barry, McPherson, Liane, Metherell, Stella, Harris, Nichola, Lake, Victoria, Radford, Elizabeth, Smallwood, Andy, Gopal, Shameer, Vassell, Katherine, Bell, Dina, Boyle, Rosalind, Douglas, Katie, Glass, Lynn, Lennon, Liz, Rattray, Austin, Lee, Emma, Jones, Danielle, Parsons, Penny, Attwood, Ben, Jefferson, Paul, Ranganathan, Mohan, Atwal, Inderjit, Campbell, Bridget, Day, Angela, Stagg, Camilla, Haynes, Emma, Ahmed, Cecilia, Clamp, Sarah, Colley, Julie, Haq, Risna, Hayes, Anne, Joseph, Sibet, Maqsood, Zahira, Hussain, Samia, Hulme, Jonathan, Domingos, Patience, Kumar, Rita, Purewal, Manjit, Taylor, Becky, Bunni, Lara, Latif, Monica, Jennings, Claire, Jose, Shilu, Marshall, Rebecca, Metryka, Aleksandra, Subramanian, Gayathri, Burgoyne, Adam, Tyler, Amanda, Waldron, Joanne, Hilltout, Paula, Evitts, Jayne, Ward, Geraldine, Bremmer, Pamela, Hawkins, Carl, Jackman, Sophie, Ogorek, Michal, Ashby, Kylie, Thornton, Lorraine, Mercer, Pauline, Halkes, Matthew, Revill, Adam, Saint, Bryony, Fletcher, Jo, Netherton, Kimberley, Chablani, Manish, Kirkby, Amy, Roper, Amanda, Szymiczek, Kinga, Sutherland, Isobel, O’Brien, Linda, Connell, Joanne, Davies, Kim, Lewis, Tracy, Omar, Zohra, Perkins, Emma, Sathe, Sonia, Davies, Ellie, Lyon, Alex, Mapfunde, Isheunesu, Willis, Charlotte, Hitchcock, Rachael, Hall, Kathryn, King, Christopher, Fagan, Andrew, Nazari, Roonak, Worsley, Lucy, Allibone, Suzanne, Kasipandian, Vidya, Patel, Amit, Cutting, Parisa, Genetu, Roman, Mac, Ainhi, Murphy, Anthony, Ward, Sinead, Butt, Fatima, Ayers, Amanda, Harrison, Wendy, Mackintosh, Katherine, North, Julie, Ashton, Lydia, Bi, Rehana, Owen, Samantha, Winmill, Helen, Scholefield, Barney, Blowing, Hannah, Williams, Erin, Duskova, Michaela, Edwards, Michelle, Rees, Alun, Thomas, Helen, Brooks, Jolene, Phipps, Janet, Brooks, Suzanne, Dennis, Catherine, Parris, Vicki, Srikaran, Sinduya, Sukha, Anisha, McGregor, Alistair, Tiongson, Gerlynn, Adams, Katie, Andrew, Benedict, Brayne, Adam, Carter, Sasha, Findlay, Louise, Fisher, Emma, Jackson, Peter, Kaye, Duncan, Parkin, Juliet, Tuckey, Victoria, Hunt, Jane, Love, Nicholas, van Koutrick, Lynne, Hanson, Ashley, Dent, Kathy, Horsley, Elizabeth, Pearson, Sandra, Spencer, Sue, Hutchinson, Dorothy, Potoczna, Dorota, Akhtar, Muhammad Nauman, Cottam, Lisa-Jayne, Sanders, Jack, Garcia, Sara Mingo, pakou, Glykeria, Filipe, Helder, Maharajh, Amitaa, de Neef, Mark, Martin, Daniel, Eastgate, Christine, Teoh, Poh Choo, Barrett, Fiona, Bradley, Clare, Donaldson, Avril, Mascarenhas, Mairi, O’Hara, Marianne, Okeefe, Laura, Clarke, Noreen, Whiteside, Jonathan, Campbell, Rachael, Matheson, Joanna, McDonald, Deborah, Patience, Donna, Rice, Polly, Clapham, Melanie, Mutch, Rachel, Craig, Hannah, Poultney, Una, Burns, Karen, Twiss, Sophie, Barton, Janet, George, Linsha, Harrop, Clare, Mathew, Sherly, Wright, David Justin, Harrison, Rachel, Toohie, Jordan, Chandler, Ben, Turnbull, Alison, Mallinson, Janine, Elliott, Kerry, Wolf-Roberts, Rebecca, Tench, Helen, Hobrok, Maria, Loosley, Ronda, McGuinness, Heather, Sims, Tanya, Afolabi, Deborah, Allison, Kathryn Sian, Anderson, Taya, Dore, Rachael, Jones, Dawn, Rogers, Naomi, Saunderson, Paula, Whitbread, Jennifer, O’Malley, Laura, Rad, Laura, Hawcutt, Daniel, Aldridge, Jonathan, Tolson, Melanie, Garrioch, Sweyn, Tomlinson, Joanne, Grosdenier, Michael, Loader, David, Kapoor, Ritoo, Hector, Gemma, Scherewode, Joslan, Sri-Chandana, Chunda, Stephenson, Lorraine, Marsh, Sarah, Rosa, Arnold Dela, Jhanji, Shaman, Bemand, Thomas, Howle, Ryan, Baikady, Ravishankar Rao, Thomas, Benjamin, Black, Ethel, Tatham, Kate, Gurram, Sambasivarao, Watson, Ekaterina, Quaid, Sheena, Saunderson, Anne, O’Brien, Rachel, Moultrie, Sam, Service, Jen, Cheyne, Clare, Odam, Miranda, Wiliams, Alison, Barnes, Nicky, Csabi, Peter, Rocha, Joana Da, Glynou, Louika, Huffenberger, Amy, Bryant, Jade, Pickard, Amy, Roe, Nicholas, Bellini, Arianna, Mayer, Anton, Burrow, Amy, Colley, Natalie, Evans, Jayne, Howlett, Alex, Khalifeh, Zeinab, Pryce, Jerldine, Gorman, Claire, Brady, Rebecca, Timlick, Elizabeth, Antoine, Pierre, Gupta, Abhinhav, Hardy, John, Houlden, Henry, Moncur, Eleanor, Tucci, Arianna, Tariq, Ambreen, Tagliavini, Emma, Ramsay, Becky, Fidler, Katy, Donnelly, Kevin, Hollis, Rebecca, Barr, Jocelyn, Boyd, Elizabeth, Irvine, Val, Shelley, Ben, Buckley, Julie, Hamilton, Charlene, Valdeavella, Kathryn, Bircham, Sarah, Liggett, Steven, Patil, Anand, Siddiq, Afshan, Goddard, Peter, Donovan, Sally, Zainy, Tala, Maleady-Crowe, Fiona, Todd, Linda, Salehi, Shahla, Elgar, Greg, Chan, Georgia, Arumugam, Prabhu, Patch, Christine, Rendon, Augusto, Bentley, David, Kingsley, Clare, Fowler, Tom A., Elliott, Paul, Tenesa, Albert, Aitkin, Emma, Aravindan, Latha, Armstrong, Ruth, Biggs, Heather, Boz, Ceilia, Brown, Adam, Chikowore, Primmy, Coutts, Audrey, Coyle, Judy, Cullum, Louise, Das, Sukamal, Day, Nicky, Donnelly, Lorna, Duncan, Esther, Finernan, Paul, Fourman, Max Head, Furlong, Anita, Furniss, James, Gallagher, Bernadette, Gilchrist, Tammy, Golightly, Ailsa, Hafezi, Katarzyna, Hamilton, Debbie, Hendry, Ross, Kearns, Naomi, Law, Dawn, Law, Rachel, Law, Sarah, Lidstone-Scott, Rebecca, Lauder, Christen, Macgillivray, Louise, Maclean, Alan, Mal, Hanning, McCafferty, Sarah, Mcmaster, Ellie, Meikle, Jen, Moore, Shona C., Murphy, Sheena, Mybaya, Hellen, Oosthuyzen, Wilna, Zheng, Chenqing, Chen, Jiantao, Paterson, Trevor, Tucker, Petra, Schon, Katherine, Stenhouse, Andrew, Das, Mihaela, Swets, Maaike, Szoor-McElhinney, Helen, Taneski, Filip, Turtle, Lance, Wackett, Tony, Ward, Mairi, Weaver, Jane, Wrobel, Nicola, Rakitko, Alexander, Ilinsky, Valery, Yermakovich, Danat, Popov, Iaroslav, Chernitsov, Alexander, Kovalenko, Elena, Vergasova, Ekaterina, Prokhorov, Alexandr, Krasnenko, Anna, Plotnikov, Nikolay, Stetsenko, Ivan, Kim, Anna, Cirulli, Elizabeth T., Schiabor Barrett, Kelly M., Bolze, Alexandre, White, Simon, Washington, Nicole L., Lu, James T., Riffle, Stephen, Tanudjaja, Francisco, Wang, Xueqing, Ramirez, Jimmy M., Leonetti, Nicole, Sandoval, Efren, Neveux, Iva, Dabe, Shaun, Grzymski, Joseph J., Joshi, Madhvi N., Dixit, Raghav D., Shah, Pranay K., Upadhyay, Kamlesh J., Chuhan, Naresh T., Desai, Kairavi J., Shah, Meenakshi R., Modi, Bhavesh, Joshi, Chaitanya G., Pandit, Ramesh J., Singh, Indra, Ansari, Afzal I., Raval, Janvi N., Patel, Zarna Z., Moreno-Estrada, Andres, Vázquez-Pérez, Joel Armando, Castillejos-López, Manuel, Aquino-Gálvez, Arnoldo, Shamah-Levy, Teresa, Ávila-Arcos, María C., Luna, María Teresa Tusié, Hidalgo-Miranda, Alfredo, Barberena-Jonas, Carmina, Quinto-Cortés, Consuelo D., Ávila-Arcos, Marco Antonio, Huerta-Chagoya, Alicia, García-García, Lourdes, Barnetche, Jesús Martinez, Alpuche-Aranda, Celia, Rivera, Juan A., Gutiérrez, Tonatiuh Barrientos, Ochoa-Guzmán, Ana, Ordoñez-Sánchez, Maria Luisa, Segura-Kato, Yayoi, Herrera-Montalvo, Luis Alonso, Mendoza-Vargas, Alfredo, Reyes-Grajeda, Juan Pablo, Cruz-Cruz, Alonso D., Velázquez-Cruz, Rafael, Torres-Espíndola, Luz María, Sierra-Vargas, Martha Patricia, Camarena, Angel, Ruiz, Víctor, Chávez-Alderete, Jaime, Jaime-Capetillo, María Esther, Guadarrama-Pérez, Cristóbal, Zúñiga-Ramos, Joaquin, Olivera-Ramírez, Alejandra, Martínez, Miguel Angel López, Serna-Muñoz, Ricardo, Garmendia, Adriana, Namkoong, Ho, Okada, Yukinori, Imoto, Seiya, Katayama, Kazuhiko, Fukunaga, Koichi, Kitagawa, Yuko, Sato, Toshiro, Hasegawa, Naoki, Kumanogoh, Atsushi, Kimura, Akinori, Ai, Masumi, Tokunaga, Katsushi, Kanai, Takanori, Miyano, Satoru, Ogawa, Seishi, Edahiro, Ryuya, Sonehara, Kyuto, Shirai, Yuya, Ishii, Makoto, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Tanaka, Hiromu, Morita, Atsuho, Lee, Ho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Mikami, Yohei, Tomono, Kazunori, Kato, Kazuto, Matsuda, Fumihiko, Takahashi, Meiko, Hizawa, Nobuyuki, Takeda, Yoshito, Hirata, Haruhiko, Shiroyama, Takayuki, Miyawaki, Satoru, Suzuki, Ken, Maeda, Yuichi, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Takahashi, Kunihiko, Anzai, Tatsuhiko, Hasegawa, Takanori, Ito, Satoshi, Koike, Ryuji, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro, Nakajima, Jun, Nannya, Yasuhito, Omae, Yosuke, Takahashi, Kazuhisa, Harada, Norihiro, Hiki, Makoto, Takagi, Haruhi, Nakamura, Ai, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Ishiguro, Takashi, Takayanagi, Noboru, Isono, Taisuke, Takaku, Yotaro, Takano, Kenji, Anan, Ryusuke, Nakajima, Yukiko, Nakano, Yasushi, Nishio, Kazumi, Ueda, Soichiro, Hayashi, Reina, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Mitamura, Keiko, Saito, Fumitake, Ueda, Tetsuya, Azuma, Masanori, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Yoshiyama, Takashi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Watanabe, Kazuyoshi, Manabe, Tadashi, Ito, Fumimaro, Fukui, Takahiro, Funatsu, Yohei, Koh, Hidefumi, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Saito, Fukuki, Yoshiya, Kazuhisa, Yoshihara, Tomoyuki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Nishi, Koichi, Nishitsuji, Masaru, Tani, Maiko, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Ogura, Takashi, Kitamura, Hideya, Murohashi, Kota, Nakachi, Ichiro, Baba, Rie, Arai, Daisuke, Fuke, Satoshi, Saito, Hiroshi, Kuwahara, Naota, Fujiwara, Akiko, Okada, Takenori, Baba, Tomoya, Noda, Junya, Mashimo, Shuko, Yagi, Kazuma, Shiomi, Tetsuya, Hashiguchi, Mizuha, Odani, Toshio, Mochimaru, Takao, Oyamada, Yoshitaka, Mori, Nobuaki, Izumi, Namiki, Nagata, Kaoru, Taki, Reiko, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Gon, Yasuhiro, Fujitani, Shigeki, Tsuchida, Tomoya, Yoshida, Toru, Kagaya, Takashi, Kita, Toshiyuki, Sakagami, Satoru, Kimizuka, Yoshifumi, Kawana, Akihiko, Nakamura, Yoshihiko, Ishikura, Hiroyasu, Takata, Tohru, Kikuchi, Takahide, Taniyama, Daisuke, Nakamura, Morio, Kodama, Nobuhiro, Kaneyama, Yasunari, Maeda, Shunsuke, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Ito, Akihiro, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Hashimoto, Naozumi, Wakahara, Keiko, Ando, Akira, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Sageshima, Hisako, Nakada, Taka-Aki, Abe, Ryuzo, Shimada, Tadanaga, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Yamasaki, Masaki, Hashimoto, Satoru, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Takada, Minoru, Kanda, Hidenori, Komase, Yuko, Sano, Fumiaki, Asano, Koichiro, Oguma, Tsuyoshi, Harada, Masahiro, Takahashi, Takeshi, Shibusawa, Takayuki, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Izumo, Takehiro, Inomata, Minoru, Awano, Nobuyasu, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Kitagawa, Yuichiro, Yoshida, Shozo, Ogura, Shinji, Nishiyama, Kei, Yoshida, Kousuke, Beppu, Satoru, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Inoue, Yoshiaki, Yamagata, Kunihiro, Chiba, Shigeru, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Shibata, Yoko, Tanino, Yoshinori, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Imamura, Tomonori, Umeda, Akira, Shimada, Hisato, Endo, Mayu, Hayashi, Shinichi, Takahashi, Mai, Nakano, Shigefumi, Yatomi, Masakiyo, Maeno, Toshitaka, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Nishida, Nao, Kawai, Yosuke, Sugiyama, Masaya, Alawneh, Laith M., Maswadeh, Kinda B., Alsoub, Fatima S., AlRawashdeh, Tala J., Esawi, Ezaldeen, Abu Alragheb, Bayan O., Maswadeh, Ahmad B., Al-Kadash, Abdulfattah, Al-Ani, Abdallah, Alsafadi, Dana B., Shahin, Mohammad A., Qtaish, Nuseibah Al, Alawneh, Fade M., Abulail, Joseph A., Zhlawi, Hadi J., Alhousani, Tasneem N., Alzuraiqi, Mohammad R., Al-Ja’afreh, Mohammad M., Allouzy, Sara K., ALjalamdeh, Mothafer, Mansour, Tareq M., Alamer, Lina M., Issa, Ali Banni, Bani younis, Fatima M., Hawari, Feras I., Hayajneh, Wail A., Obeidat, Nathir M., Ahram, Mamoun, Zhlawi, Moh’d Wahib J., Alshaer, Walhan, Al-Kasasbeh, Malak M., Naffa, Randa G., Ismail, Mohammad A., Abdullah, Mohammed S., Ismail, Said I., Obeidat, Ma’en, Hernández Cordero, Ana I., Sin, Don D., Bossé, Yohan, Joubert, Philippe, Hao, Ke, Nickle, David, Timens, Wim, van den Berge, Maarten, Feng, Yen-Chen Anne, Mercader, Josep, Weiss, Scott T., Karlson, Elizabeth W., Smoller, Jordan W., Murphy, Shawn N., Meigs, James B., Woolley, Ann E., Green, Robert C., Mandla, Ravi, Schroeder, Philip, Perez, Emma F., Lee, Seung Hyuk T., Flores-Silva, Fernando Daniel, Chiquete, Erwin, Cantú-Brito, Carlos, Sifuentes-Osornio, José, de León-Garduño, Alfredo Ponce, Román-Montes, Carla Marina, Chávez-Manzanera, Emma, Velasco, Donaji Gómez, Martagón-Rosado, Alexandro, Cruz-Bautista, Ivette, Gómez-Pérez, Francisco Javier, Díaz-Olavarrieta, Claudia, Valdés, Paloma Almeda, Muñóz-Hernández, Linda Liliana, Mehta, Roopa Pravin, Elías-López, Daniel, Tusié-Luna, Teresa, Pajukanta, Päivi, Sukhatme, Mihir G., Moreno-Macías, Hortensia, Ruth, Johnson, González-Behn-Eschenburg, Sebastián, García-Grimshaw, Miguel, Guillen-Pineda, Luz Elizabeth, de los Ángeles Vargas-Martínez, María, Rodríguez, Maribel, Rodríguez-Guillén, Rosario, Ordoñez, María Luisa, Rajme-López, Sandra, González-Lara, María Fernanda, Luna-Moreno, Dalia, de Jesús Suárez López, Jannet, Guillén-Quintero, Daniela Mariel, Vega, Juan, Duran-Coyote, Salvador, Guerra-García, María Teresa, Durán-Gómez, Michelle, Vigueras-Hernández, Alma, Ramírez-Jiménez, Marco Eduardo, Grajeda-González, Samara Lissete, Ramos-Galicia, Enrique Manuel, Ramírez-Carrillo, Martha Fernanda, Fernandez-Ruiz, Juan, Chirino-Pérez, Amanda, Romero-Molina, Ángel Omar, Zavaleta, David Alejandro Fuentes, Jaramillo, María Andrea Mac Donald, López, Katia Jarely Prieto, Incontri-Abraham, Diego, Rosado, Wendy Natalia, Catalán, María Alonso, Aguilar, Sonia Evelyn Vital, Zamudio, Ileana Paola Montero, Ruíz-Ruíz, Eduardo, de Jesús Carrera García, Kevin, Guerrero, Cristina Villarreal, Martínez, Ana Isabel Rodríguez, Moscoso-Sánchez, Rogelio, del Consuelo Rodríguez Mancilla, María, Villa, Antonio, Luna-Ramírez, Samuel Alejandro, Hernández-Hernández, Sergio, Frias, Erika, Campos, Alejandro, Morales-Sosa, Paola Alessandra, Toxqui-Merchant, Luis Enrique, García, Karla, Pasaniuc, Bogdan, Butte, Manish J., Geschwind, Daniel H., Aguilar-Salinas, Carlos A., Heidecker, Bettina, Kurth, Florian, Sander, Leif E., Skurk, Carsten, Landmesser, Ulf, Karadeniz, Zehra, Wang, Xiaomin, Poller, Wolfgang, Suwalski, Phillip, Ripke, Stephan, Braun, Alice, Kraft, Julia, Mayer, Alena, Lippert, Lena J., Helbig, Elisa T., Thibeault, Charlotte, Awasthi, Swapnil, Mbarek, Hamdi, Saad, Chadi, Al-Sarraj, Yaser, Badji, Radja Messai, Al-Muftah, Wadha, Thani, Asma Al, Afifi, Nahla, Sadiq, Fouzia, Khan, Mohammad I., Bhutta, Muhammad J., Khan, Hania, Khan, Madeeha, Ain, Quratul, Junaid, Ayesha, Khan, Ejaz A., Sypniewski, Mateusz, Lejman, Adrian, Zawadzki, Paweł, Sztromwasser, Paweł, Król, Zbigniew, Dobosz, Paula, Stojak, Joanna, Flores, Carlos, Carracedo, Ángel, Aguilar, Carlos, Arranz, María J., Baptista-Rosas, Raúl C., Bezerra, Joao F., Bezerra, Marcos A. C., Brugada, Ramón, Bustos, Matilde, Castano, Luis, Conde-Vicente, Rosa, Cordero-Lorenzana, M. Lourdes, De Martino-Rodríguez, Alba, Domínguez-Garrido, Elena, Fariñas, María Carmen, Gil-Fournier, Belén, Herrero, María José, Lattig, María Claudia, Martín-López, Caridad, Martín, Vicente, Martinez-Nieto, Oscar, Martinez-Lopez, Iciar, Mazzeu, Juliana F., Macías, Eleuterio Merayo, Cuerda, Victor Moreno, Silbiger, Vivian N., Oliveira, Silviene F., Parellada, Mara, Santos, Ney P. C., Pérez-Matute, Patricia, Perez, Patricia, Perucho, Teresa, Porras-Hurtado, Gloria L., Pujol, Aurora, Fernández-Rodríguez, Amanda, Jimenez-Sousa, María A., Rodríguez-Ruiz, Emilio, Rodriguez-Artalejo, Fernando, Rodriguez-Garcia, José A., Ruiz-Cabello, Francisco, Soria, José Manuel, Tamayo, Eduardo, Teper, Alejandro, Torres-Tobar, Lilian, Urioste, Miguel, Yáñez, Zuleima, Zarate, Ruth, Guillen-Navarro, Encarna, Ayuso, Carmen, González-Neira, Anna, Riancho, José A., Rojas-Martinez, Augusto, Lapunzina, Pablo, Cruz, Raquel, Diz-de Almeida, Silvia, Ceballos, Francisco C., Lorenzo-Salazar, José M., González-Montelongo, Rafaela, Quintela, Inés, Pita, Guillermo, Gago-Domínguez, Manuela, Porras, Marta Sevilla, Tenorio-Castaño, Jair Antonio, Nevado, Julian, Aguado, Jose María, Aguilera-Albesa, Sergio, Almadana, Virginia, Almoguera, Berta, Alvarez, Nuria, Andreu-Bernabeu, Álvaro, Arango, Celso, Artiga, Maria-Jesus, Barreda-Sánchez, María, Belhassen-Garcia, Moncef, Boix-Palop, Lucía, Brion, María, Carbonell, Cristina, Castelao, Jose E., Cortes-Sanchez, Jose L., Corton, Marta, Darnaude, M. Teresa, del Campo-Pérez, Victor, de Bustamante, Aranzazu Diaz, Luchessi, Andre D., Eiros, Rocío, Sanabria, Gladys Mercedes Estigarribia, Fernández-Robelo, Uxía, Fernández-Villa, Tania, Gómez-Arrue, Javier, Álvarez, Beatriz González, de Quirós, Fernan Gonzalez Bernaldo, González-Peñas, Javier, Gutiérrez-Bautista, Juan F., Herrero-Gonzalez, Antonio, Borja, Anabel Liger, Lopez-Rodriguez, Rosario, Mancebo, Esther, Martinez-Resendez, Michel F., Martinez-Perez, Angel, Minguez, Pablo, Ortega-Paino, Eva, Paz-Artal, Estela, Pérez-Tomás, M. Elena, Pinsach-Abuin, Mel·lina, Pompa-Mera, Ericka N., León, Soraya Ramiro, Resino, Salvador, Fernandes, Marianne R., Ruiz-Hornillos, Javier, Ryan, Pablo, Souto, Juan Carlos, Tamayo-Velasco, Alvaro, Taracido-Fernandez, Juan Carlos, Valencia-Ramos, Juan, de Heredia, Miguel López, Pedersen, Ole B., Erikstrup, Christian, Ostrowski, Sisse R., Stefansson, Kari, Mikkelsen, Susan, Sørensen, Erik, Burgos, Celia, Andersen, Steffen, Brugdorf, Kristoffer, Hansen, Thomas F., Hjalgrim, Henrik, Jemec, Gregor B., Nyegaard, Mette, Werge, Thomas, Johansson, Pär I., Didriksen, Maria, Schwinn, Michael, Jacobsen, Rikke L., Hindhede, Lotte, Rostgaard, Klaus, Gudbjartsson, Daniel, Stefánsson, Hreinn, Þorsteinsdóttir, Unnur, Nielsen, Kaspar R., Bruun, Mie Topholm, Dinh, Khoa M., Larsen, Margit A. H., Sækmose, Susanne G., Zeberg, Hugo, Nkambul, Lindo, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Tardif, Nicolas, Rooyackers, Olav, Grip, Jonathan, Maricic, Tomislav, Heid, Iris M., Wagner, Ralf, Überla, Klaus, Winkler, Thomas W., Wiegrebe, Simon, Gorski, Mathias, Stark, Klaus J., Peterhoff, David, Einhauser, Sebastian, Niller, Hans-Helmut, Beileke, Stephanie, Johnson, Ruth, Freimer, Nelson, Ding, Yi, Chiu, Alec, Chang, Timothy S., Boutros, Paul, Karczewski, Konrad J., Martin, Alicia R., Wilson, Daniel J., Spencer, Chris C. A., Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Atkinson, Elizabeth G., Tsuo, Kristin, Baya, Nikolas, Turley, Patrick, Gupta, Rahul, Walters, Raymond K., Palmer, Duncan S., Sarma, Gopal, Solomonson, Matthew, Cheng, Nathan, Lu, Wenhan, Churchhouse, Claire, Goldstein, Jacqueline I., King, Daniel, Zhou, Wei, Seed, Cotton, Daly, Mark J., Finucane, Hilary, Bryant, Sam, Satterstrom, F. Kyle, Band, Gavin, Earle, Sarah G., Lin, Shang-Kuan, Arning, Nicolas, Koelling, Nils, Armstrong, Jacob, Rudkin, Justine K., Callier, Shawneequa, Cusick, Caroline, Fernandez-Cadenas, Israel, Planas, Anna M., Perez-Tur, Jordi, Llucià-Carol, Laia, Cullell, Natalia, Muiño, Elena, Cárcel-Márquez, Jara, DeDiego, Marta L., Iglesias, Lara Lloret, Soriano, Alex, Rico, Veronica, Agüero, Daiana, Bedini, Josep L., Lozano, Francisco, Domingo, Carlos, Robles, Veronica, Ruiz-Jaén, Francisca, Márquez, Leonardo, Gomez, Juan, Coto, Eliecer, Albaiceta, Guillermo M., García-Clemente, Marta, Dalmau, David, Arranz, Maria J., Dietl, Beatriz, Serra-Llovich, Alex, Soler-Palacin, Pere, Colobran, Roger, Martin-Nalda, Andrea, Parra-Martínez, Alba, Bernardo, David, Rojo, Silvia, Fiz-López, Aida, Arribas-Rodriguez, Elisa, Cal-Sabater, Paloma, Segura, Tomás, González-Villar, Esther, Serrano-Heras, Gemma, Martí-Fàbregas, Joan, Jiménez-Xarrié, Elena, de Felipe Mimbrera, Alicia, Masjuan, Jaime, García-Madrona, Sebastian, Domínguez-Mayoral, Anna, Villalonga, Joan Montaner, and Menéndez-Valladares, Paloma
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- 2023
24. Credit Union Capital, Insolvency, and Mergers Before and After Share Insurance
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WILCOX, James A, WILCOX, James A, WILCOX, James A, and WILCOX, James A
- Abstract
From their beginnings in 1908, U.S. credit unions have grown into a trillion-dollar industry with more than 100 million members. Despite many similarities, credit unions have always differed fundamentally from banks. One fundamental difference was that share accounts in credit unions, unlike bank deposits, were not debt. Thus, credit unions had options to delay and discount payments to account holders. Those options were one reason why, when thousands of banks failed, no credit unions failed during the Great Depression. Insolvency came to credit unions only after share accounts became federally insured in 1971. Insurance and its associated regulations had larger effects on the structure of the credit union industry than it had on the banking industry. Insurance turned bank deposits from risky debt into riskless debt. Insurance largely turned credit union share accounts from risky equity into riskless debt. Thus, insurance introduced insolvency risk and insolvency to credit unions. Before federal insurance, many credit unions voluntarily liquidated, and of those, only about one-fifth imposed losses on their members. After federal insurance took effect in 1971, voluntary liquidations of solvent credit unions became rare. To reduce insolvency risk and losses to the share insurance fund, regulators enabled and encouraged mergers of both strong and weak credit unions. They also discouraged new credit unions. These regulatory responses moved the credit union industry from high entry and low merger rates to near-zero entry and high merger rates. We further argue that the proximate causes of regulation differed between credit unions and banks. Major bank regulations almost always, and only, happened following banking crises. In contrast, major credit union regulations rarely followed crises, but rather usually followed prosperity in the credit union industry. Insurance is one of the examples we give.
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- 2022
25. Policies and Prescriptions for Safe and Sound Banking: Shocks, Lessons, and Prospects
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WILCOX, James A, WILCOX, James A, WILCOX, James A, and WILCOX, James A
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- 2022
26. Pro-cyclicality, Banks’ Reporting Discretion, and “Safety in Similarity”
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WILCOX, James A, WILCOX, James A, Luengnaruemitchai, Pipat, WILCOX, James A, WILCOX, James A, and Luengnaruemitchai, Pipat
- Abstract
During recessions, either declines in actual capital or increases in required capital may intensify pressures on banks. One way for banks to boost their capital ratios is by reducing their lending. However, one effect of systematic reductions in the supply of bank loans during recessions would likely be to accentuate the magnitudes of macroeconomic fluctuations. To reduce this source of “procyclicality”, it has been proposed that Basel II include “escape clauses”. Such clauses might, for example, operate so as to raise required bank capital during macroeconomic expansions and reduce it during downturns. Apart from formal escape clauses, procyclicality might be reduced or even reversed in practice if banks exercise sufficient discretion in reporting their charge-offs and loan loss provisions. We propose two hypotheses about the past cyclicality of such discretion. We hypothesize that individual banks tended to report fewer charge-offs and provisions when the banking system was troubled than when it was generally healthier. That suggested our second hypothesis: Banks tended to cluster more when the banking industry was troubled. Banks would maximize the value of their reporting discretion by clustering more then; being similar to other banks raised the likelihood that a bank would be able to exert reporting discretion when it encountered difficulties, because other, similar banks, and thus the banking system as a whole, would likely be troubled at the same time. We found some support for our hypotheses at large U.S. banks. During the late 1980s, when banking was troubled and bank capital ratios were low, individual banks reported fewer charge-offs, ceteris paribus, when the capital ratios of their peers were lower. During the late 1990s, in contrast, when capital ratios were higher, charge-offs at individual banks were not systematically related to the capital ratios of peer banks. We also found that the equity and the asset betas of individual banks tended to cluster
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- 2022
27. Interfacility Transport of Critically Ill Patients.
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Wilcox, Susan R, Wilcox, Susan R, Wax, Randy S, Meyer, Michael T, Stocking, Jacqueline C, Baez, Amado Alejandro, Cohen, Jason, Moss, M Michele, Frakes, Michael A, Scruth, Elizabeth A, Weir, William B, Zonies, David, Guyette, Francis X, Kaplan, Lewis J, Cannon, Jeremy W, Wilcox, Susan R, Wilcox, Susan R, Wax, Randy S, Meyer, Michael T, Stocking, Jacqueline C, Baez, Amado Alejandro, Cohen, Jason, Moss, M Michele, Frakes, Michael A, Scruth, Elizabeth A, Weir, William B, Zonies, David, Guyette, Francis X, Kaplan, Lewis J, and Cannon, Jeremy W
- Abstract
ObjectivesTo assess recent advances in interfacility critical care transport.Data sourcesPubMed English language publications plus chapters and professional organization publications.Study selectionManuscripts including practice manuals and standard (1990-2021) focused on interfacility transport of critically ill patients.Data extractionReview of society guidelines, legislative requirements, objective measures of outcomes, and transport practice standards occurred in work groups assessing definitions and foundations of interfacility transport, transport team composition, and transport specific considerations. Qualitative analysis was performed to characterize current science regarding interfacility transport.Data synthesisThe Task Force conducted an integrative review of 496 manuscripts combined with 120 from the authors' collections including nonpeer reviewed publications. After title and abstract screening, 40 underwent full-text review, of which 21 remained for qualitative synthesis.ConclusionsSince 2004, there have been numerous advances in critical care interfacility transport. Clinical deterioration may be mitigated by appropriate patient selection, pretransport optimization, and transport by a well-resourced team and vehicle. There remains a dearth of high-quality controlled studies, but notable advances in monitoring, en route management, transport modality (air vs ground), as well as team composition and training serve as foundations for future inquiry. Guidance from professional organizations remains uncoupled from enforceable regulations, impeding standardization of transport program quality assessment and verification.
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- 2022
28. Frequency of Detection of Respiratory Pathogens in Clinically Healthy Show Horses Following a Multi-County Outbreak of Equine Herpesvirus-1 Myeloencephalopathy in California.
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Wilcox, Abigail, Wilcox, Abigail, Barnum, Samantha, Wademan, Cara, Corbin, Rachel, Escobar, Edlin, Hodzic, Emir, Schumacher, Stephen, Pusterla, Nicola, Wilcox, Abigail, Wilcox, Abigail, Barnum, Samantha, Wademan, Cara, Corbin, Rachel, Escobar, Edlin, Hodzic, Emir, Schumacher, Stephen, and Pusterla, Nicola
- Abstract
Actively shedding healthy horses have been indicated as a possible source of respiratory pathogen outbreak, transmission, and spread. Using nasal swabs from clinically healthy sport horses submitted for qPCR testing after an outbreak of equine herpesvirus-1 (EHV-1) myeloencephalopathy (EHM) in the spring of 2022, this study aimed to identify the rate of clinically healthy horses shedding common and less characterized respiratory pathogens within the sport horse population to better understand their role in outbreaks. Swabs were collected during a required quarantine and testing period, according to the United States Equestrian Federation (USEF), and showed return-to-competition requirements. Common respiratory pathogens, such as equine influenza virus (EIV), EHV-4, and equine rhinitis B virus (ERBV), were found at low but stable frequencies within previously reported ranges, whereas EHV-1 and Streptococcus equi subspecies equi (S. equi) were found at or above previously reported frequencies. Less characterized respiratory pathogens, such as EHV-2, EHV-5, and S. equi subspecies zooepidemicus (S. zooepidemicus), were found within previously reported ranges. Common respiratory pathogens, especially EHV-1 following the multiple EHM outbreaks, were found to be circulating in clinically healthy sport horse populations, reflecting their silent transmission. The strategy of quarantine and EHV-1 qPCR testing of clinically healthy horses was successful at eliminating additional EHM outbreaks and facilitating safe return to competition with no reported respiratory disease outbreaks following the subsequent shows in California.
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- 2022
29. Whole-genome sequencing reveals host factors underlying critical COVID-19
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Kousathanas, A., Pairo-Castineira, E., Rawlik, K., Stuckey, A., Odhams, C. A., Walker, S., Russell, C. D., Malinauskas, T., Wu, Y., Millar, J., Shen, X., Elliott, K. S., Griffiths, F., Oosthuyzen, W., Morrice, K., Keating, S., Wang, B., Rhodes, D., Klaric, L., Zechner, M., Parkinson, N., Siddiq, A., Goddard, P., Donovan, S., Maslove, D., Nichol, A., Semple, M. G., Zainy, T., Maleady-Crowe, F., Todd, L., Salehi, S., Knight, J., Elgar, G., Chan, G., Arumugam, P., Patch, C., Rendon, A., Bentley, D., Kingsley, C., Kosmicki, J. A., Horowitz, J. E., Baras, A., Abecasis, G. R., Ferreira, M. A. R., Justice, A., Mirshahi, T., Oetjens, M., Rader, D. J., Ritchie, M. D., Verma, A., Fowler, T. A., Shankar-Hari, M., Summers, C., Hinds, C., Horby, P., Mcauley, D., Montgomery, H., Openshaw, P. J. M., Elliott, P., Walsh, T., Tenesa, A., Fawkes, A., Murphy, L., Rowan, K., Ponting, C. P., Vitart, V., Wilson, J. F., Yang, J., Bretherick, A. D., Scott, R. H., Hendry, S. C., Moutsianas, L., Law, A., Caulfield, M. J., Baillie, J. K., Begg, C., Ling, L., Pereira, A. C., Aravindan, L., Armstrong, R., Biggs, H., Boz, C., Brown, A., Clark, R., Coutts, A., Coyle, J., Cullum, L., Das, S., Day, N., Donnelly, L., Duncan, E., Finernan, P., Fourman, M. H., Furlong, A., Furniss, J., Gallagher, B., Gilchrist, T., Golightly, A., Hafezi, K., Hamilton, D., Hendry, R., Law, D., Law, R., Law, S., Lidstone-Scott, R., Macgillivray, L., Maclean, A., Mal, H., Mccafferty, S., Mcmaster, E., Meikle, J., Moore, S. C., Murphy, S., Hellen, M., Zheng, C., Chen, J., Paterson, T., Schon, K., Stenhouse, A., Das, M., Swets, M., Szoor-McElhinney, H., Taneski, F., Turtle, L., Wackett, T., Ward, M., Weaver, J., Wrobel, N., Arbane, G., Bociek, A., Campos, S., Grau, N., Jones, T. O., Lim, R., Marotti, M., Ostermann, M., Whitton, C., Alldis, Z., Astin-Chamberlain, R., Bibi, F., Biddle, J., Blow, S., Bolton, M., Borra, C., Bowles, R., Burton, M., Choudhury, Y., Collier, D., Cox, A., Easthope, A., Ebano, P., Fotiadis, S., Gurasashvili, J., Halls, R., Hartridge, P., Kallon, D., Kassam, J., Lancoma-Malcolm, I., Matharu, M., May, P., Mitchelmore, O., Newman, T., Patel, M., Pheby, J., Pinzuti, I., Prime, Z., Prysyazhna, O., Shiel, J., Taylor, M., Tierney, C., Wood, S., Zak, A., Zongo, O., Bonner, S., Hugill, K., Jones, J., Liggett, S., Headlam, E., Bandla, N., Gellamucho, M., Davies, M., Thompson, C., Abdelrazik, M., Bakthavatsalam, D., Elhassan, M., Ganesan, A., Haldeos, A., Moreno-Cuesta, J., Purohit, D., Vincent, R., Xavier, K., Kumar, R., Frater, Alessia, Saleem, M., Carter, D., Jenkins, S., Lamond, Z., Wall, A., Fernandez-Roman, J., Hamilton, D. O., Johnson, E., Johnston, B., Martinez Guzman, Maria Loreto, Mulla, S., Shaw, D., Waite, A. A. C., Waugh, V., Welters, I. D., Williams, K., Cavazza, A., Cockrell, M., Corcoran, E., Depante, M., Finney, C., Jerome, E., Mcphail, M., Nayak, M., Noble, H., O'Reilly, K., Pappa, E., Saha, R., Saha, S., Smith, Jenovia Amisti, Knighton, A., Antcliffe, D., Banach, D., Brett, S., Coghlan, P., Fernandez, Z., Gordon, A., Rojo, R., Arias, S. S., Templeton, M., Meredith, M., Morris, L., Ryan, L., Clark, A., Sampson, J., Peters, C., Dent, M., Langley, M., Ashraf, Sana, Wei, S., Andrew, A., Bashyal, A., Davidson, N., Hutton, P., Mckechnie, S., Wilson, J., Baptista, D., Crowe, R., Fernandes, R., Herdman-Grant, R., Joseph, A., O'Connor, D., Allen, M., Loveridge, A., Mckenley, I., Morino, E., Naranjo, A., Simms, R., Sollesta, K., Swain, A., Venkatesh, H., Khera, J., Fox, J., Andrew, G., Barclay, L., Callaghan, M., Campbell, R., Clark, S., Hope, D., Marshall, L., Mcculloch, C., Briton, K., Singleton, J., Birch, S., Brimfield, L., Daly, Z., Pogson, D., Rose, S., Nown, A., Battle, C., Brinkworth, E., Harford, R., Murphy, C., Newey, L., Rees, T., Williams, M., Arnold, S., Polgarova, P., Stroud, K., Meaney, E., Jones, M., Ng, A., Agrawal, S., Pathan, N., White, D., Daubney, E., Elston, K., Grauslyte, L., Hussain, M., Phull, M., Pogreban, T., Rosaroso, L., Salciute, E., Franke, G., Wong, J., George, A., de Gordoa, L. O. -R., Peasgood, E., Phillips, C., Bates, M., Dasgin, J., Gill, J., Nilsson, A., Scriven, J., Collins, A., Khaliq, W., Gude, E. T., Delgado, C. C., Dawson, D., Ding, L., Durrant, G., Ezeobu, O., Farnell-Ward, S., Harrison, A., Kanu, R., Leaver, S., Maccacari, E., Manna, S., Saluzzio, R. P., Queiroz, J., Samakomva, T., Sicat, C., Texeira, J., Da Gloria, E. F., Lisboa, A., Rawlins, J., Mathew, J., Kinch, A., Hurt, W. J., Shah, N., Clark, V., Thanasi, M., Yun, N., Patel, K., Bennett, S., Goodwin, E., Jackson, M., Kent, A., Tibke, C., Woodyatt, W., Zaki, A., Abraheem, A., Bamford, P., Cawley, K., Dunmore, C., Faulkner, M., Girach, R., Jeffrey, H., Jones, R., London, E., Nagra, I., Nasir, F., Sainsbury, H., Smedley, C., Patel, T., Smith, M., Chukkambotla, S., Kazi, A., Hartley, J., Dykes, J., Hijazi, M., Keith, S., Khan, M., Ryan-Smith, J., Springle, P., Thomas, J., Truman, N., Saad, S., Coleman, D., Fine, C., Matt, R., Gay, B., Dalziel, J., Ali, S., Goodchild, D., Harling, R., Bhatterjee, R., Goddard, W., Davison, C., Duberly, S., Hargreaves, J., Bolton, R., Davey, M., Golden, D., Seaman, R., Cherian, S., Cutler, S., Heron, A. E., Roynon-Reed, A., Szakmany, T., Williams, G., Richards, O., Cheema, Y., Brooke, H., Buckley, S., Suarez, J. C., Charlesworth, R., Hansson, K., Norris, J., Poole, A., Rose, A., Sandhu, R., Sloan, B., Smithson, E., Thirumaran, M., Wagstaff, V., Metcalfe, A., Brunton, M., Caterson, J., Coles, H., Frise, M., Rai, S. 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R., Chavan, S., Laisk, T., Lall, K., Lepamets, M., Magi, R., Esko, T., Reimann, E., Milani, Luca, Alavere, H., Metsalu, K., Puusepp, M., Metspalu, A., Naaber, P., Laane, E., Pesukova, J., Peterson, P., Kisand, K., Tabri, J., Allos, R., Hensen, K., Starkopf, J., Ringmets, I., Tamm, A., Kallaste, A., Bochud, P. -Y., Rivolta, C., Bibert, S., Quinodoz, M., Kamdar, D., Boillat, N., Nussle, S. G., Albrich, W., Suh, N., Neofytos, D., Erard, V., Voide, C., de Cid, R., Galvan-Femenia, I., Blay, N., Carreras, A., Cortes, B., Farre, X., Sumoy, L., Moreno, V., Mercader, J. M., Guindo-Martinez, M., Torrents, D., Kogevinas, M., Garcia-Aymerich, J., Castano-Vinyals, G., Dobano, C., Renieri, A., Mari, F., Fallerini, C., Daga, S., Benetti, E., Baldassarri, M., Fava, F., Frullanti, E., Valentino, Francesca, Doddato, G., Giliberti, A., Tita, R., Amitrano, S., Bruttini, M., Croci, S., Meloni, I., Mencarelli, Marta, Rizzo, C. L., Pinto, A. M., Beligni, G., Tommasi, A., Sarno, L. D., Palmieri, Marco, Carriero, M. L., Alaverdian, D., Busani, S., Bruno, R., Vecchia, M., Belli, M. A., Picchiotti, N., Sanarico, M., Gori, Mario, Furini, S., Mantovani, Susanna, Ludovisi, S., Mondelli, M. U., Castelli, F., Quiros-Roldan, E., Antoni, M. D., Zanella, I., Vaghi, M., Rusconi, S., Siano, M., Montagnani, F., Emiliozzi, A., Fabbiani, M., Rossetti, Barbara, Bargagli, E., Bergantini, L., D'Alessandro, Michele, Cameli, P., Bennett, D., Anedda, F., Marcantonio, S., Scolletta, S., Franchi, Francesca, Mazzei, M. A., Guerrini, S., Conticini, E., Cantarini, L., Frediani, B., Tacconi, D., Spertilli, C., Feri, M., Donati, Andrea, Scala, R., Guidelli, L., Spargi, G., Corridi, M., Nencioni, C., Croci, L., Bandini, M., Caldarelli, G. P., Piacentini, P., Desanctis, E., Cappelli, S., Canaccini, A., Verzuri, A., Anemoli, V., Ognibene, A., Pancrazzi, A., Lorubbio, M., Monforte, A. D., Miraglia, F. G., Girardis, M., Venturelli, S., Cossarizza, A., Antinori, Armando, Vergori, A., Gabrieli, A., Riva, A., Francisci, D., Schiaroli, E., Paciosi, F., Scotton, P. G., Andretta, F., Panese, S., Scaggiante, R., Gatti, F., Parisi, S. G., Baratti, S., Monica, M. D., Piscopo, C., Capasso, Monica, Russo, R., Andolfo, I., Iolascon, A., Fiorentino, Giuseppe, Carella, M., Castori, M., Merla, G., Squeo, G. M., Aucella, F., Raggi, P., Marciano, C., Perna, Raffaella, Bassetti, M., Biagio, A. D., Sanguinetti, Maurizio, Masucci, Luca, Valente, S., Mandala, M., Giorli, A., Salerni, L., Zucchi, P., Parravicini, P., Menatti, E., Trotta, T., Giannattasio, F., Coiro, G., Lena, Francesco, Coviello, D. A., Mussini, C., Martinelli, E., Mancarella, S., Tavecchia, L., Crotti, L., Gabbi, Chiara, Rizzi, M., Maggiolo, F., Ripamonti, D., Bachetti, T., Rovere, M. T. L., Sarzi-Braga, S., Bussotti, M., Ceri, S., Pinoli, P., Raimondi, F., Biscarini, F., Stella, A., Zguro, K., Capitani, K., Suardi, C., Dei, S., Parati, G., Ravaglia, S., Artuso, R., Botta, Giovanni, Di Domenico, Pasqualina, Rancan, I., Perrella, A., Bianchi, F., Romani, D., Bergomi, P., Catena, E., Colombo, R., Tanfoni, M., Vincenti, A., Ferri, C., Grassi, D., Pessina, Gloria, Tumbarello, Mario, Di Pietro, Maria Luisa, Sabrina, R., Luchi, S., Barbieri, Cristiano, Acquilini, D., Andreucci, E., Segala, F. V., Tiseo, G., Falcone, M., Lista, Maddalena, Poscente, M., De Vivo, O., Petrocelli, Paolo, Guarnaccia, A., Baroni, S., Smith, A. V., Boughton, A. P., Li, K. W., Lefaive, J., Annis, A., Chittoor, G., Josyula, N. S., Leader, J. B., Carey, D. J., Gass, M. C., Cantor, M. N., Yadav, A., van Heel, D. A., Hunt, K. A., Mason, D., Huang, Q. Q., Finer, S., Trivedi, B., Griffiths, C. J., Martin, H. C., Wright, J., Trembath, R. C., Soranzo, N., Zhao, J. H., Butterworth, A. S., Danesh, J., Di Angelantonio, E., Franke, L., Boezen, M., Deelen, P., Claringbould, A., Lopera, E., Warmerdam, R., Vonk, J. M., van Blokland, I., Lanting, P., Ori, A. P. S., Zollner, S., Wang, J., Beck, A., Peloso, G., Ho, Y. -L., Sun, Y. V., Huffman, J. E., O'Donnell, C. J., Cho, K., Tsao, P., Gaziano, J. M., Nivard, M., de Geus, E., Bartels, M., Hottenga, J. J., Weiss, S. T., Karlson, E. W., Smoller, J. W., Green, R. C., Feng, Y. -C. A., Mercader, J., Murphy, S. N., Meigs, J. B., Woolley, A. E., Perez, E. F., Rader, D., Li, B., Verma, S. S., Lucas, A., Bradford, Y., Zeberg, H., Frithiof, R., Hultstrom, M., Lipcsey, M., Tardif, N., Rooyackers, O., Grip, J., Maricic, T., Karczewski, K. J., Atkinson, E. G., Tsuo, K., Baya, N., Turley, P., Gupta, R., Callier, S., Walters, R. K., Palmer, D. S., Sarma, G., Cheng, N., Lu, W., Bryant, S., Churchhouse, C., Cusick, C., Goldstein, J. I., King, D., Seed, C., Finucane, H., Martin, A. R., Satterstrom, F. K., Wilson, D. J., Armstrong, J., Rudkin, J. K., Band, G., Earle, S. G., Lin, S. -K., Arning, N., Crook, D. W., Wyllie, D. H., O'Connell, A. M., Spencer, C. C. A., Koelling, N., Fowler, T., Pasko, D., Ball, C. A., Hong, E. L., Rand, K., Girshick, A., Guturu, H., Baltzell, A. H., Roberts, G., Park, D., Coignet, M., Mccurdy, S., Knight, S., Partha, R., Rhead, B., Zhang, M., Berkowitz, N., Gaddis, M., Noto, K., Ruiz, L., Pavlovic, M., Sloofman, L. G., Charney, A. W., Beckmann, N. D., Schadt, E. E., Jordan, D. M., Thompson, R. C., Gettler, K., Abul-Husn, N. S., Ascolillo, S., Buxbaum, J. D., Chaudhary, K., Cho, J. H., Itan, Y., Kenny, E. E., Belbin, G. M., Sealfon, S. C., Sebra, R. P., Salib, I., Collins, B. L., Levy, T., Britvan, B., Keller, K., Tang, L., Peruggia, M., Hiester, L. L., Niblo, K., Aksentijevich, A., Labkowsky, A., Karp, A., Zlatopolsky, M., Preuss, M., Loos, R. J. F., Nadkarni, G. N., Do, R., Hoggart, C., Choi, S., Underwood, S. J., O'Reilly, P., Huckins, L. M., Zyndorf, M., Daly, M. J., Neale, B. M., Ganna, A., Frater A., Martinez M. L., Smith J., Ashraf S., Singh J., Kay A., Lorusso R., Ali A., Williams H., Barberis L., Wood D. (ORCID:0000-0001-8588-8931), Latif M., Finn S., Taylor A., Tucci A., Adams E. L., Milani L. (ORCID:0000-0003-0218-458X), Valentino F., Mencarelli M. A., Palmieri M. (ORCID:0000-0001-8263-336X), Gori M., Mantovani S., Rossetti B., D'Alessandro M., Franchi F., Donati A., Antinori A. (ORCID:0000-0002-6019-2417), Capasso M., Fiorentino G., Perna R., Sanguinetti M. (ORCID:0000-0002-9780-7059), Masucci L. (ORCID:0000-0002-8358-6726), Lena F. (ORCID:0000-0001-5528-319X), Gabbi C., Botta G., Di Domenico P., Pessina G., Tumbarello M. (ORCID:0000-0002-9519-8552), Di Pietro M. (ORCID:0000-0002-3893-8788), Barbieri C., Lista M., and Petrocelli P.
- Abstract
Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.
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- 2022
30. DYNAMICS, STABILITY, AND MAINTENANCE MECHANISMS OF SUPER LONG-LIVED OCEAN VORTICES
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Margolina, Tetyana, Radko, Timour, Wilcox, Lucas C., Brown, Justin M., Jacobs, Gregg, Naval Research Laboratory - Stennis Space Center, Oceanography (OC), Gulliver, Larry T., Margolina, Tetyana, Radko, Timour, Wilcox, Lucas C., Brown, Justin M., Jacobs, Gregg, Naval Research Laboratory - Stennis Space Center, Oceanography (OC), and Gulliver, Larry T.
- Abstract
Ocean variability in the form of coherent mesoscale eddies is still poorly understood despite more than a century of persistent interest and undeniable geophysical significance. These eddies propagate for thousands of miles and distribute vast amounts of nutrients and energy throughout the world’s oceans. Most intriguing is how analytical theories and physical arguments suggest that larger vortices, those with radii greater than 75 km, should become unstable and break down in the span of months, yet they are observed to last for years. This research explores two phenomena that contribute to the longevity of these features. First is their ability to adjust to ambient large-scale flows—a feature that determines the eddy’s endurance. The second aspect is the role small-scale, irregular topography plays in vortex dynamics. We demonstrate that rough seafloor stabilizes surface-intensified vortices by restricting the motion in the deep layer, thereby allowing the upper ring to perpetuate unhindered. Using an analytical parameterization, we show how this "sandpaper effect" can be accounted for in quasi-geostrophic and full Navier-Stokes models. This research will ultimately allow the U.S. Navy to improve global ocean forecasts without dramatically increasing the spatial resolution., Civilian, Department of the Navy, Approved for public release. Distribution is unlimited.
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- 2023
31. Benchmarking of survival outcomes following Haematopoietic Stem Cell Transplantation (HSCT): an update of the ongoing project of the European Society for Blood and Marrow Transplantation (EBMT) and Joint Accreditation Committee of ISCT and EBMT (JACIE).
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Saccardi, R., Putter, H., Eikema, D.J., Busto, M.P., McGrath, E., Middelkoop, B., Adams, G., Atlija, M., Ayuk, F.A., Baldomero, H., Beguin, Y., Cámara, R. de la, Cedillo, Á., Balari, A.M.S., Chabannon, C., Corbacioglu, S., Dolstra, H., Duarte, R.F., Dulery, R., Greco, R., Gusi, A., Hamad, N., Kenyon, M., Kröger, N., Labopin, M., Lee, J., Ljungman, P., Manson, L., Mensil, F., Milpied, N., Mohty, M., Oldani, E., Orchard, K., Passweg, J., Pearce, R., Latour, R.P. de, Poirel, H.A., Rintala, T., Rizzo, J.D., Ruggeri, A., Sanchez-Martinez, C., Sanchez-Guijo, F., Sánchez-Ortega, I., Trnková, M., Ferreiras, D.V., Wilcox, L., Wreede, L.C. de, Snowden, J.A., Saccardi, R., Putter, H., Eikema, D.J., Busto, M.P., McGrath, E., Middelkoop, B., Adams, G., Atlija, M., Ayuk, F.A., Baldomero, H., Beguin, Y., Cámara, R. de la, Cedillo, Á., Balari, A.M.S., Chabannon, C., Corbacioglu, S., Dolstra, H., Duarte, R.F., Dulery, R., Greco, R., Gusi, A., Hamad, N., Kenyon, M., Kröger, N., Labopin, M., Lee, J., Ljungman, P., Manson, L., Mensil, F., Milpied, N., Mohty, M., Oldani, E., Orchard, K., Passweg, J., Pearce, R., Latour, R.P. de, Poirel, H.A., Rintala, T., Rizzo, J.D., Ruggeri, A., Sanchez-Martinez, C., Sanchez-Guijo, F., Sánchez-Ortega, I., Trnková, M., Ferreiras, D.V., Wilcox, L., Wreede, L.C. de, and Snowden, J.A.
- Abstract
01 juni 2023, Item does not contain fulltext, From 2016 EBMT and JACIE developed an international risk-adapted benchmarking program of haematopoietic stem cell transplant (HSCT) outcome to provide individual EBMT Centers with a means of quality-assuring the HSCT process and meeting FACT-JACIE accreditation requirements relating to 1-year survival outcomes. Informed by previous experience from Europe, North America and Australasia, the Clinical Outcomes Group (COG) established criteria for patient and Center selection, and a set of key clinical variables within a dedicated statistical model adapted to the capabilities of the EBMT Registry. The first phase of the project was launched in 2019 to test the acceptability of the benchmarking model through assessment of Centers' performance for 1-year data completeness and survival outcomes of autologous and allogeneic HSCT covering 2013-2016. A second phase was delivered in July 2021 covering 2015-2019 and including survival outcomes. Reports of individual Center performance were shared directly with local principal investigators and their responses were assimilated. The experience thus far has supported the feasibility, acceptability and reliability of the system as well as identifying its limitations. We provide a summary of experience and learning so far in this 'work in progress', as well as highlighting future challenges of delivering a modern, robust, data-complete, risk-adapted benchmarking program across new EBMT Registry systems.
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- 2023
32. Charged pion electric polarizability from four-point functions in lattice QCD
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Lee, Frank X., Alexandru, Andrei, Culver, Chris, Wilcox, Walter, Lee, Frank X., Alexandru, Andrei, Culver, Chris, and Wilcox, Walter
- Abstract
Polarizabilities reveal valuable information on the internal structure of hadrons in terms of charge and current distributions. For neutral hadrons, the standard approach is the background field method. But for a charged hadron, its acceleration under the the applied field complicates the isolation of the polarization energy. In this work, we explore an alternative method based on four-point functions in lattice QCD. The approach offers a transparent picture on how polarizabilities arise from quark and gluon interactions. We carry out a proof-of-concept simulation on the electric polarizability of a charged pion, using quenched Wilson action on a $24^3\times 48$ lattice at $\beta=6.0$ with pion mass from 1100 to 370 MeV. We show in detail the evaluation and analysis of the four-point correlation functions and report results on charge radius and electric polarizability. Our results from connected diagrams suggest that charged pion $\alpha_E$ is due to a large cancellation between elastic and inelastic contributions, leaving a small and positive value that has a relatively mild pion mass dependence., Comment: 23 pages, 12 figures, 2 tables
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- 2023
33. A growing plastic smog, now estimated to be over 170 trillion plastic particles afloat in the world's oceans-Urgent solutions required
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Eriksen, Marcus, Cowger, Win, Erdle, Lisa M., Coffin, Scott, Villarrubia-Gómez, Patricia, Moore, Charles J., Carpenter, Edward J., Day, Robert H., Thiel, Martin, Wilcox, Chris, Eriksen, Marcus, Cowger, Win, Erdle, Lisa M., Coffin, Scott, Villarrubia-Gómez, Patricia, Moore, Charles J., Carpenter, Edward J., Day, Robert H., Thiel, Martin, and Wilcox, Chris
- Abstract
As global awareness, science, and policy interventions for plastic escalate, institutions around the world are seeking preventative strategies. Central to this is the need for precise global time series of plastic pollution with which we can assess whether implemented policies are effective, but at present we lack these data. To address this need, we used previously published and new data on floating ocean plastics (n = 11,777 stations) to create a global time-series that estimates the average counts and mass of small plastics in the ocean surface layer from 1979 to 2019. Today’s global abundance is estimated at approximately 82–358 trillion plastic particles weighing 1.1–4.9 million tonnes. We observed no clear detectable trend until 1990, a fluctuating but stagnant trend from then until 2005, and a rapid increase until the present. This observed acceleration of plastic densities in the world’s oceans, also reported for beaches around the globe, demands urgent international policy interventions.
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- 2023
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34. Stem cell plasticity, acetylation of H3K14, and de novo gene activation rely on KAT7.
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Kueh, AJ, Bergamasco, MI, Quaglieri, A, Phipson, B, Li-Wai-Suen, CSN, Lönnstedt, IM, Hu, Y, Feng, Z-P, Woodruff, C, May, RE, Wilcox, S, Garnham, AL, Snyder, MP, Smyth, GK, Speed, TP, Thomas, T, Voss, AK, Kueh, AJ, Bergamasco, MI, Quaglieri, A, Phipson, B, Li-Wai-Suen, CSN, Lönnstedt, IM, Hu, Y, Feng, Z-P, Woodruff, C, May, RE, Wilcox, S, Garnham, AL, Snyder, MP, Smyth, GK, Speed, TP, Thomas, T, and Voss, AK
- Abstract
In the conventional model of transcriptional activation, transcription factors bind to response elements and recruit co-factors, including histone acetyltransferases. Contrary to this model, we show that the histone acetyltransferase KAT7 (HBO1/MYST2) is required genome wide for histone H3 lysine 14 acetylation (H3K14ac). Examining neural stem cells, we find that KAT7 and H3K14ac are present not only at transcribed genes but also at inactive genes, intergenic regions, and in heterochromatin. KAT7 and H3K14ac were not required for the continued transcription of genes that were actively transcribed at the time of loss of KAT7 but indispensable for the activation of repressed genes. The absence of KAT7 abrogates neural stem cell plasticity, diverse differentiation pathways, and cerebral cortex development. Re-expression of KAT7 restored stem cell developmental potential. Overexpression of KAT7 enhanced neuron and oligodendrocyte differentiation. Our data suggest that KAT7 prepares chromatin for transcriptional activation and is a prerequisite for gene activation.
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- 2023
35. ACTIVE STEALTH IN SUBMERGED ENVIRONMENTS: A NUMERICAL INVESTIGATION
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Bassett, Robert L., Austin, Anthony, Wilcox, Lucas C., Applied Mathematics (MA), Hyde, Dylan E., Bassett, Robert L., Austin, Anthony, Wilcox, Lucas C., Applied Mathematics (MA), and Hyde, Dylan E.
- Abstract
Enemy acoustic sensors can present issues for U.S. Navy submarines that attempt to operate undetected. One potential way to address this threat is to use active noise cancellation to mask submarine noise. This thesis examines the feasibility of this idea by numerically solving a partial differential equation–constrained optimization problem to compute a masking signal for a given source signal as the signal propagates through a simulated 2D ocean environment. We examine how the location and type of source affect the strength of the cancellation. In particular, we show that it is possible to effectively cancel the sound from a source within a specific region—such as the area in proximity to an acoustic sensor—provided that the source’s location and sound profile are known., Captain, United States Army, Approved for public release. Distribution is unlimited.
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- 2023
36. The enhanced future Flows and Groundwater dataset: development and evaluation of nationally consistent hydrological projections based on UKCP18
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Hannaford, Jamie, Mackay, Jonathan D., Ascott, Matthew, Bell, Victoria A., Chitson, Thomas, Cole, Steven, Counsell, Christian, Durant, Mason, Jackson, Christopher R., Kay, Alison L., Lane, Rosanna A., Mansour, Majdi, Moore, Robert, Parry, Simon, Rudd, Alison C., Simpson, Michael, Facer-Childs, Katie, Turner, Stephen, Wallbank, John R., Wells, Steven, Wilcox, Amy, Hannaford, Jamie, Mackay, Jonathan D., Ascott, Matthew, Bell, Victoria A., Chitson, Thomas, Cole, Steven, Counsell, Christian, Durant, Mason, Jackson, Christopher R., Kay, Alison L., Lane, Rosanna A., Mansour, Majdi, Moore, Robert, Parry, Simon, Rudd, Alison C., Simpson, Michael, Facer-Childs, Katie, Turner, Stephen, Wallbank, John R., Wells, Steven, and Wilcox, Amy
- Abstract
This paper details the development and evaluation of the enhanced future FLows and Groundwater (eFLaG) dataset of nationally consistent hydrological projections for the UK, based on the latest UK Climate Projections (UKCP18). The projections are derived from a range of hydrological models. For river flows, multiple models (Grid-to-Grid, PDM (Probability Distributed Model) and GR (Génie Rural; both four- and six-parameter versions, GR4J and GR6J)) are used to provide an indication of hydrological model uncertainty. For groundwater, two models are used, a groundwater level model (AquiMod) and a groundwater recharge model (ZOODRM: zooming object-oriented distributed-recharge model). A 12-member ensemble of transient projections of present and future (up to 2080) daily river flows, groundwater levels and groundwater recharge was produced using bias-corrected data from the UKCP18 regional (12 km) climate ensemble. Projections are provided for 200 river catchments, 54 groundwater level boreholes and 558 groundwater bodies, all sampling across the diverse hydrological and geological conditions of the UK. An evaluation was carried out to appraise the quality of hydrological model simulations against observations and also to appraise the reliability of hydrological models driven by the regional climate model (RCM) ensemble in terms of their capacity to reproduce hydrological regimes in the current period. The dataset was originally conceived as a prototype climate service for drought planning for the UK water sector and so has been developed with drought, low river flow and low groundwater level applications as the primary objectives. The evaluation metrics show that river flows and groundwater levels are, for the majority of catchments and boreholes, well simulated across the flow and level regime, meaning that the eFLaG dataset could be applied to a wider range of water resources research and management contexts, pending a full evaluation for the designated purpose. Only a
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- 2023
37. The enhanced future Flows and Groundwater dataset: development and evaluation of nationally consistent hydrological projections based on UKCP18
- Author
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Hannaford, Jamie, Mackay, Jonathan D., Ascott, Matthew, Bell, Victoria A., Chitson, Thomas, Cole, Steven, Counsell, Christian, Durant, Mason, Jackson, Christopher R., Kay, Alison L., Lane, Rosanna A., Mansour, Majdi, Moore, Robert, Parry, Simon, Rudd, Alison C., Simpson, Michael, Facer-Childs, Katie, Turner, Stephen, Wallbank, John R., Wells, Steven, Wilcox, Amy, Hannaford, Jamie, Mackay, Jonathan D., Ascott, Matthew, Bell, Victoria A., Chitson, Thomas, Cole, Steven, Counsell, Christian, Durant, Mason, Jackson, Christopher R., Kay, Alison L., Lane, Rosanna A., Mansour, Majdi, Moore, Robert, Parry, Simon, Rudd, Alison C., Simpson, Michael, Facer-Childs, Katie, Turner, Stephen, Wallbank, John R., Wells, Steven, and Wilcox, Amy
- Abstract
This paper details the development and evaluation of the enhanced future FLows and Groundwater (eFLaG) dataset of nationally consistent hydrological projections for the UK, based on the latest UK Climate Projections (UKCP18). The projections are derived from a range of hydrological models. For river flows, multiple models (Grid-to-Grid, PDM (Probability Distributed Model) and GR (Génie Rural; both four- and six-parameter versions, GR4J and GR6J)) are used to provide an indication of hydrological model uncertainty. For groundwater, two models are used, a groundwater level model (AquiMod) and a groundwater recharge model (ZOODRM: zooming object-oriented distributed-recharge model). A 12-member ensemble of transient projections of present and future (up to 2080) daily river flows, groundwater levels and groundwater recharge was produced using bias-corrected data from the UKCP18 regional (12 km) climate ensemble. Projections are provided for 200 river catchments, 54 groundwater level boreholes and 558 groundwater bodies, all sampling across the diverse hydrological and geological conditions of the UK. An evaluation was carried out to appraise the quality of hydrological model simulations against observations and also to appraise the reliability of hydrological models driven by the regional climate model (RCM) ensemble in terms of their capacity to reproduce hydrological regimes in the current period. The dataset was originally conceived as a prototype climate service for drought planning for the UK water sector and so has been developed with drought, low river flow and low groundwater level applications as the primary objectives. The evaluation metrics show that river flows and groundwater levels are, for the majority of catchments and boreholes, well simulated across the flow and level regime, meaning that the eFLaG dataset could be applied to a wider range of water resources research and management contexts, pending a full evaluation for the designated purpose. Only a
- Published
- 2023
38. Pharmacologically Treated Anxiety and Depression in People Diagnosed with von Willebrand Disease: Matched Cohort Study
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Hagberg,Katrina Wilcox, Jick,Susan, Ãzen,Gülden, Du,Ping, Hagberg,Katrina Wilcox, Jick,Susan, Ãzen,Gülden, and Du,Ping
- Abstract
Katrina Wilcox Hagberg,1 Susan Jick,1,2 Gülden Ãzen,3 Ping Du3 1Boston Collaborative Drug Surveillance Program, Lexington, MA, 02421, USA; 2Boston University School of Public Health, Boston, MA, 02118, USA; 3Takeda Development Center Americas, Inc., Cambridge, MA, 02139, USACorrespondence: Susan Jick, Boston Collaborative Drug Surveillance Program, 11 Muzzey Street, Lexington, MA, 02421, USA, Tel +1 781 862 6660, Fax +1 781 862 1680, Email sjick@bu.eduBackground: People diagnosed with von Willebrand disease (VWD) have reduced quality of life versus the general population, and there is limited evidence of increased rates of anxiety and/or depression among people diagnosed with VWD.Aim: To understand the association between VWD and mental health outcomes.Design and Setting: A retrospective cohort study was conducted using the UK Clinical Practice Research Datalink (CPRD) GOLD database (1988â 2016).Methods: People diagnosed with VWD were matched 1:10 to randomly selected people in the database without VWD based on sex, birth year ± 2 years, CPRD record start year ± 2 years, and general practice attended. Individuals were followed from VWD diagnosis or match date to censoring (first event date, CPRD end date, or death). Treated anxiety and treated depression were identified by a diagnostic Read Code and a prescription for anxiety/depression medication recorded within 90 days of each other, after VWD diagnosis/match date.Results: Treated anxiety was recorded in 89 of 1119 (8.0%) people diagnosed with VWD and 624 of 10,423 (6.0%) without VWD (age- and sex-adjusted incidence rate ratio [IRR], 1.37; 95% confidence interval [CI], 1.10â 1.71). Treated depression was recorded in 119 of 1083 (11.0%) people diagnosed with VWD and 846 of 9845 (8.6%) without VWD (adjusted IRR, 1.35; 95% CI, 1.11â 1.63). Females aged 20â 39 and 0â 19 years were at greatest risk for treated anxiety and treated depression, respectively.Conclusion: Higher rates of treated anxiety and dep
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- 2023
39. Higher doses of tisagenlecleucel are associated with improved outcomes: a report from the pediatric real-world CAR consortium.
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Stefanski, Heather E, Stefanski, Heather E, Eaton, Anne, Baggott, Christina, Rossoff, Jenna, Verneris, Michael R, Prabhu, Snehit, Pacenta, Holly L, Phillips, Christine L, Talano, Julie-An, Moskop, Amy, Margossian, Steven P, Myers, Gary Douglas, Karras, Nicole A, Brown, Patrick A, Qayed, Muna, Hermiston, Michelle, Satwani, Prakash, Krupski, M Christa, Keating, Amy K, Wilcox, Rachel, Rabik, Cara A, Fabrizio, Vanessa A, Chinnabhandar, Vasant, Goksenin, A Yasemin, Curran, Kevin J, Mackall, Crystal L, Laetsch, Theodore W, Schultz, Liora M, Stefanski, Heather E, Stefanski, Heather E, Eaton, Anne, Baggott, Christina, Rossoff, Jenna, Verneris, Michael R, Prabhu, Snehit, Pacenta, Holly L, Phillips, Christine L, Talano, Julie-An, Moskop, Amy, Margossian, Steven P, Myers, Gary Douglas, Karras, Nicole A, Brown, Patrick A, Qayed, Muna, Hermiston, Michelle, Satwani, Prakash, Krupski, M Christa, Keating, Amy K, Wilcox, Rachel, Rabik, Cara A, Fabrizio, Vanessa A, Chinnabhandar, Vasant, Goksenin, A Yasemin, Curran, Kevin J, Mackall, Crystal L, Laetsch, Theodore W, and Schultz, Liora M
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Remarkable complete response rates have been shown with tisagenlecleucel, a chimeric antigen receptor (CAR) T-cell therapy targeting CD19, in patients up to age 26 years with refractory/relapsed B-cell acute lymphoblastic leukemia; it is US Food and Drug Administration approved for this indication. Currently, patients receive a single dose of tisagenlecleucel across a wide dose range of 0.2 to 5.0 × 106 and 0.1 to 2.5 × 108 CAR T cells per kg for patients ≤50 and >50 kg, respectively. The effect of cell dose on survival and remission is not yet well established. Our primary goal was to determine if CAR T-cell dose affects overall survival (OS), event-free survival (EFS), or relapse-free-survival (RFS) in tisagenlecleucel recipients. Retrospective data were collected from Pediatric Real World CAR Consortium member institutions and included 185 patients infused with commercial tisagenlecleucel. The median dose of viable transduced CAR T cells was 1.7 × 106 CAR T cells per kg. To assess the impact of cell dose, we divided responders into dose quartiles: 0.134 to 1.300 × 106 (n = 48 [27%]), 1.301 to 1.700 × 106 (n = 46 [26%]), 1.701 to 2.400 × 106 (n = 43 [24%]), and 2.401 to 5.100 × 106 (n = 43 [24%]). OS, EFS, and RFS were improved in patients who received higher doses of tisagenlecleucel (P = .031, .0079, and .0045, respectively). Higher doses of tisagenlecleucel were not associated with increased toxicity. Because the current tisagenlecleucel package insert dose range remains broad, this work has implications in regard to targeting higher cell doses, within the approved dose range, to optimize patients' potential for long-standing remission.
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- 2023
40. MR Multitasking-based multi-dimensional assessment of cardiovascular system (MT-MACS) with extended spatial coverage and water-fat separation.
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Hu, Zhehao, Hu, Zhehao, Xiao, Jiayu, Mao, Xianglun, Xie, Yibin, Kwan, Alan C, Song, Shlee S, Fong, Michael W, Wilcox, Alison G, Li, Debiao, Christodoulou, Anthony G, Fan, Zhaoyang, Hu, Zhehao, Hu, Zhehao, Xiao, Jiayu, Mao, Xianglun, Xie, Yibin, Kwan, Alan C, Song, Shlee S, Fong, Michael W, Wilcox, Alison G, Li, Debiao, Christodoulou, Anthony G, and Fan, Zhaoyang
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PurposeTo extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment.MethodsMT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated.ResultsMT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects.ConclusionThe refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validatio
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- 2023
41. Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement.
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Knauert, Melissa P, Knauert, Melissa P, Ayas, Najib T, Bosma, Karen J, Drouot, Xavier, Heavner, Mojdeh S, Owens, Robert L, Watson, Paula L, Wilcox, M Elizabeth, Anderson, Brian J, Cordoza, Makayla L, Devlin, John W, Elliott, Rosalind, Gehlbach, Brian K, Girard, Timothy D, Kamdar, Biren B, Korwin, Amy S, Lusczek, Elizabeth R, Parthasarathy, Sairam, Spies, Claudia, Sunderram, Jag, Telias, Irene, Weinhouse, Gerald L, Zee, Phyllis C, Knauert, Melissa P, Knauert, Melissa P, Ayas, Najib T, Bosma, Karen J, Drouot, Xavier, Heavner, Mojdeh S, Owens, Robert L, Watson, Paula L, Wilcox, M Elizabeth, Anderson, Brian J, Cordoza, Makayla L, Devlin, John W, Elliott, Rosalind, Gehlbach, Brian K, Girard, Timothy D, Kamdar, Biren B, Korwin, Amy S, Lusczek, Elizabeth R, Parthasarathy, Sairam, Spies, Claudia, Sunderram, Jag, Telias, Irene, Weinhouse, Gerald L, and Zee, Phyllis C
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Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.
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- 2023
42. Assessing the impacts of a water, sanitation, and hygiene (WASH) intervention on changing behavior in Bihar, India
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Wilcox, Emily Rose and Wilcox, Emily Rose
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Access to safe water, sanitation, and hygiene (WASH) is a fundamental human right and a critical component of public and environmental health. Inadequate access to WASH facilities and practices can give rise to preventable diarrheal and waterborne diseases, which can have severe consequences on individuals' health and well-being. This is especially true in low- and middle-income countries such as India. To address these issues, the S.M. Sehgal Foundation identified water quality and hygiene needs in Bihar, India, and thus launched a behavior change intervention called "WASH for Healthy Homes." The intervention aimed to promote the use of silver-ceramic pot filters and safe handwashing practices in five communities of the Vaishali District. While behavior change is a common approach to address WASH issues, evaluating the outcomes of such interventions is crucial for determining the most effective strategies and conditions under which they can be successful. Therefore, this study assessed the effectiveness of the WASH for Healthy Homes intervention and identified factors that influenced its success. A mixed methods approach was utilized that combined statistical analyses of pre- and post-intervention survey data with a thematic analysis of interview and focus group discussion data. Results demonstrated that the intervention was successful in increasing the adoption of the silver-ceramic pot filter and overall safe handwashing practices within the study communities. Success of the WASH for Health Homes intervention was facilitated by participants' health concerns, trust in the field coordinator and social peers, the aesthetic appeal of the treated water, and repeated intervention messaging. However, adoption of intervention behaviors was hindered by several factors, including economic barriers, gender roles in decision-making, the effects of children and elderly in the household, and low attendance during intervention sessions. The research findings provide valuable in
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- 2023
43. Interactions between atmospheric composition and climate change – Progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
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Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, Forster, Piers M., Fiedler, Stephanie, Naik, Vaishali, O'Connor, Fiona M., Smith, Christopher J., Pincus, Robert, Griffiths, Paul, Kramer, Ryan, Takemura, Toshihiko, Allen, Robert J., Im, Ulas, Kasoar, Matthew, Modak, Angshuman, Turnock, Steven, Voulgarakis, Apostolos, Watson-Parris, Duncan, Westervelt, Daniel M., Wilcox, Laura J., Zhao, Alcide, Collins, William J., Schulz, Michael, Myhre, Gunnar, and Forster, Piers M.
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The climate science community aims to improve our understanding of climate change due to anthropogenic influences on atmospheric composition and the Earth's surface. Yet not all climate interactions are fully understood and diversity in climate model experiments persists as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article synthesizes current challenges and emphasizes opportunities for advancing our understanding of climate change and model diversity. The perspective of this article is based on expert views from three multi-model intercomparison projects (MIPs) – the Precipitation Driver Response MIP (PDRMIP), the Aerosol and Chemistry MIP (AerChemMIP), and the Radiative Forcing MIP (RFMIP). While there are many shared interests and specialisms across the MIPs, they have their own scientific foci and specific approaches. The partial overlap between the MIPs proved useful for advancing the understanding of the perturbation-response paradigm through multi-model ensembles of Earth System Models of varying complexity. It specifically facilitated contributions to the research field through sharing knowledge on best practices for the design of model diagnostics and experimental strategies across MIP boundaries, e.g., for estimating effective radiative forcing. We discuss the challenges of gaining insights from highly complex models that have specific biases and provide guidance from our lessons learned. Promising ideas to overcome some long-standing challenges in the near future are kilometer-scale experiments to better simulate circulation-dependent processes where it is possible, and machine learning approaches for faster and better sub-grid scale parameterizations where they are needed. Both would improve our ability to adopt a smart experimental design with an optimal tradeoff between resolution, complexity and simulation length. Future experiments can be evaluated and improved with sophisticated methods that lever
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- 2023
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44. ACTIVE STEALTH IN SUBMERGED ENVIRONMENTS: A NUMERICAL INVESTIGATION
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Bassett, Robert L., Austin, Anthony, Wilcox, Lucas C., Applied Mathematics (MA), Hyde, Dylan E., Bassett, Robert L., Austin, Anthony, Wilcox, Lucas C., Applied Mathematics (MA), and Hyde, Dylan E.
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Enemy acoustic sensors can present issues for U.S. Navy submarines that attempt to operate undetected. One potential way to address this threat is to use active noise cancellation to mask submarine noise. This thesis examines the feasibility of this idea by numerically solving a partial differential equation–constrained optimization problem to compute a masking signal for a given source signal as the signal propagates through a simulated 2D ocean environment. We examine how the location and type of source affect the strength of the cancellation. In particular, we show that it is possible to effectively cancel the sound from a source within a specific region—such as the area in proximity to an acoustic sensor—provided that the source’s location and sound profile are known.
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- 2023
45. Room Impulse Response Interpolation
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Thor Wilcox, Daníel and Thor Wilcox, Daníel
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In Virtual Reality (VR) systems, the incorporation of acoustics allows for the generation of audio-visual stimuli, facilitating applications in engineering, architecture, and design. The goal of virtual acoustics is to create a realistic sound field in continuous space. Realistic virtual acoustic environments can be produced with wave-based acoustic simulations. However, rendering a sound field with a dense grid of room impulse responses (RIRs) in real-time is slow and memory-intensive. Conventionally, a more sparsely spaced grid of RIRs is used and as a workaround linear interpolation between the nearest RIRs is performed, allowing users to listen at an arbitrary location. However, the linear interpolation method reduces the quality of the sound field as it does not produce natural-sounding RIRs. The aim of this thesis is therefore to answer the question of whether we are able to achieve a better interpolation technique than linear interpolation using a machine learning approach. In this thesis, we present a novel neural network-based method for interpolating between Room Impulse Responses (RIRs). The networks were trained using RIRs from a wave-based simulation of a single 3D room and developed through a series of experiments. The experimental process was performed in three distinct stages. Firstly, we explored various representations of the RIRs: unprocessed RIRs, Short-time Fourier transform (STFT) of RIRs, and encoded STFT of the RIRs using an autoencoder. Secondly, we examined several different neural network architectures: Multi-layer perception, residual neural network, autoencoder, and U-Net. Additionally, we experimented with training the networks in a Generative Adversary Network (GAN) setting. Thirdly, we experimented with different sizes of the best-performing architecture. Results show that using an STFT representation of the RIRs combined with a residual neural network architecture yielded the most optimal results. Furthermore, we were able to outperf, Inom Virtuell Verklighet (VR) möjliggör användningen av akustik skapandet av audiovisuell stimuli, vilket underlättar tillämpningar inom ingenjörsvetenskap, arkitektur och design. Målet med virtuell akustik är att skapa ett verklighetstroget och kontinuerligt ljudfält. Verklighetstrogna virtuella akustiska miljöer kan skapas med hjälp av vågbaserade akustiska simuleringar. Men att återge ett ljudfält med ett tätt rutnät av Room Impulse Responses (RIRs) i realtid är långsamt och minneskrävande. Konventionellt används ett rutnät med glesare avstånd av RIR, och som en lösning utförs linjär interpolation mellan de närmaste RIR:erna, vilket tillåter användare att lyssna på en godtycklig plats. Den linjära interpolationen minskar dock kvaliteten på ljudfältet eftersom den inte producerar naturligt ljudande RIR:er. Syftet med detta examensarbete är därför att besvara frågan om vi kan finna en bättre interpolationsteknik än linjär interpolation med hjälp av en maskininlärningsmetod. I detta examensarbete presenterar vi en ny metod för interpolering mellan Room Impulse Responses (RIR:er) baserad på neurala nätverk. De neurala nätverken tränades med hjälp av RIR:er från en vågbaserad simulering av ett enskilt 3D-rum och utvecklades genom en serie experiment. Experimenten utfördes i tre steg. Först undersöktes olika representationer av RIR:er: obearbetade RIR:er, korttids fouriertransform (STFT) av RIR:er och kodade STFT av RIR:er med hjälp av en autoencoder. Det andra steget innefattade undersökningen av flera olika neurala nätverksarkitekturer: Multi-layer perception, residual neural network, autoencoder och U-Net. Dessutom experimenterade vi med att träna nätverken i en GAN-miljö (Generative Adversary Network). I det tredje steget experimenterade vi med olika storlekar på den mest effektiva arkitekturen. Resultaten visar att användning av en STFT-representation av RIR:er kombinerat med en residual neural nätverksarkitektur resulterade i de mest optimala resultaten. Dessutom
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- 2023
46. On the lack of stratospheric dynamical variability in low-top versions of the CMIP5 models
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Charlton-Perez, Andrew J., Baldwin, Mark P., Birner, Thomas, Black, Robert X., Butler, Amy H., Calvo Fernández, Natalia, Davis, Nicholas A., Gerber, Edwin P., Gillett, Nathan, Hardiman, Steven, Kim, Junsu, Krüger, Kirstin, Lee, Yun-Young, Manzini, Elisa, McDaniel, Brent A., Polvani, Lorenzo, Reichler, Thomas, Shaw, Tiffany A., Sigmond, Michael, Son, Seok-Woo, Toohey, Matthew, Wilcox, Laura, Yoden, Shigeo, Christiansen, Bo, Lott, François, Shindell, Drew, Yukimoto, Seiji, Watanabe, Shingo, Charlton-Perez, Andrew J., Baldwin, Mark P., Birner, Thomas, Black, Robert X., Butler, Amy H., Calvo Fernández, Natalia, Davis, Nicholas A., Gerber, Edwin P., Gillett, Nathan, Hardiman, Steven, Kim, Junsu, Krüger, Kirstin, Lee, Yun-Young, Manzini, Elisa, McDaniel, Brent A., Polvani, Lorenzo, Reichler, Thomas, Shaw, Tiffany A., Sigmond, Michael, Son, Seok-Woo, Toohey, Matthew, Wilcox, Laura, Yoden, Shigeo, Christiansen, Bo, Lott, François, Shindell, Drew, Yukimoto, Seiji, and Watanabe, Shingo
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© 2013 American Geophysical Union. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available the model output listed in Table 1. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. A. J. C.-P. and L. J. W. were supported by an National Centre for Atmospheric Science CMIP5 grant. M. P. B. was funded by NSF under the US CLIVAR program and the Office of Polar Programs. T. B. and N. A. D. acknowledge support by the U.S. National Science Foundation. The research efforts of R. X. B., B. A. M. & Y.-Y. L. were conducted under support by the U.S. Department of Energy, Office of Biological and Environmental Research, Award No. DE-FOA000024 and by the National Science Foundation Grant, ARC-1107384. N. C. was supported by the Spanish Ministry of Science and Innovation (MCINN) through the CGL2008-05968-C02-01 project. E. P. G. was supported by the National Science Foundation. The work of M. T. and K. K. contributes to the BMBF joint research project MiKlip within the project ALARM through the grant 01LP1130B. The work of S. C. H. was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). We also acknowledge the European Commission's 7th Framework Programme, under Grant Agreement number 226520, COMBINE project which supplied some data not available from the CMIP5 archive. We also thank Gerard Devine (NCAS-CMS) for help with accessing and parsing meta-data information from the models., We describe the main differences in simulations of stratospheric climate and variability by models within the fifth Coupled Model Intercomparison Project (CMIP5) that have a model top above the stratopause and relatively fine stratospheric vertical resolution (high-top), and those that have a model top below the stratopause (low-top). Although the simulation of mean stratospheric climate by the two model ensembles is similar, the low-top model ensemble has very weak stratospheric variability on daily and interannual time scales. The frequency of major sudden stratospheric warming events is strongly underestimated by the low-top models with less than half the frequency of events observed in the reanalysis data and high-top models. The lack of stratospheric variability in the low-top models affects their stratosphere-troposphere coupling, resulting in short-lived anomalies in the Northern Annular Mode, which do not produce long-lasting tropospheric impacts, as seen in observations. The lack of stratospheric variability, however, does not appear to have any impact on the ability of the low-top models to reproduce past stratospheric temperature trends. We find little improvement in the simulation of decadal variability for the high-top models compared to the low-top, which is likely related to the fact that neither ensemble produces a realistic dynamical response to volcanic eruptions., National Centre for Atmospheric Science, NSF under the US CLIVAR program, U.S. National Science Foundation, U.S. Department of Energy, Office of Biological and Environmental Research, National Science Foundation, Spanish Ministry of Science and Innovation (MCINN), National Science Foundation, BMBF, Joint DECC/Defra Met Office Hadley Centre Climate Programme, European Commission, NSF under Office of Polar Program, Depto. de Física de la Tierra y Astrofísica, Fac. de Ciencias Físicas, TRUE, pub
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- 2023
47. Screening for Dilated Cardiomyopathy in At-Risk First-Degree Relatives.
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Ni, Hanyu, Ni, Hanyu, Jordan, Elizabeth, Kinnamon, Daniel, Cao, Jinwen, Haas, Garrie, Hofmeyer, Mark, Kransdorf, Evan, Ewald, Gregory, Morris, Alanna, Owens, Anjali, Lowes, Brian, Stoller, Douglas, Tang, W, Garg, Sonia, Trachtenberg, Barry, Shah, Palak, Pamboukian, Salpy, Sweitzer, Nancy, Wheeler, Matthew, Wilcox, Jane, Katz, Stuart, Pan, Stephen, Jimenez, Javier, Fishbein, Daniel, Smart, Frank, Gottlieb, Stephen, Judge, Daniel, Moore, Charles, Huggins, Gordon, Hershberger, Ray, Wang, Jessica, Ni, Hanyu, Ni, Hanyu, Jordan, Elizabeth, Kinnamon, Daniel, Cao, Jinwen, Haas, Garrie, Hofmeyer, Mark, Kransdorf, Evan, Ewald, Gregory, Morris, Alanna, Owens, Anjali, Lowes, Brian, Stoller, Douglas, Tang, W, Garg, Sonia, Trachtenberg, Barry, Shah, Palak, Pamboukian, Salpy, Sweitzer, Nancy, Wheeler, Matthew, Wilcox, Jane, Katz, Stuart, Pan, Stephen, Jimenez, Javier, Fishbein, Daniel, Smart, Frank, Gottlieb, Stephen, Judge, Daniel, Moore, Charles, Huggins, Gordon, Hershberger, Ray, and Wang, Jessica
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BACKGROUND: Cardiovascular screening is recommended for first-degree relatives (FDRs) of patients with dilated cardiomyopathy (DCM), but the yield of FDR screening is uncertain for DCM patients without known familial DCM, for non-White FDRs, or for DCM partial phenotypes of left ventricular enlargement (LVE) or left ventricular systolic dysfunction (LVSD). OBJECTIVES: This study examined the yield of clinical screening among reportedly unaffected FDRs of DCM patients. METHODS: Adult FDRs of DCM patients at 25 sites completed screening echocardiograms and ECGs. Mixed models accounting for site heterogeneity and intrafamilial correlation were used to compare screen-based percentages of DCM, LVSD, or LVE by FDR demographics, cardiovascular risk factors, and proband genetics results. RESULTS: A total of 1,365 FDRs were included, with a mean age of 44.8 ± 16.9 years, 27.5% non-Hispanic Black, 9.8% Hispanic, and 61.7% women. Among screened FDRs, 14.1% had new diagnoses of DCM (2.1%), LVSD (3.6%), or LVE (8.4%). The percentage of FDRs with new diagnoses was higher for those aged 45 to 64 years than 18 to 44 years. The age-adjusted percentage of any finding was higher among FDRs with hypertension and obesity but did not differ statistically by race and ethnicity (16.2% for Hispanic, 15.2% for non-Hispanic Black, and 13.1% for non-Hispanic White) or sex (14.6% for women and 12.8% for men). FDRs whose probands carried clinically reportable variants were more likely to be identified with DCM. CONCLUSIONS: Cardiovascular screening identified new DCM-related findings among 1 in 7 reportedly unaffected FDRs regardless of race and ethnicity, underscoring the value of clinical screening in all FDRs.
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- 2023
48. The Regional Aerosol Model Intercomparison Project (RAMIP)
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Wilcox, Laura J., Allen, Robert J., Samset, Bjørn H., Bollasina, Massimo A., Griffiths, Paul T., Keeble, James, Lund, Marianne T., Makkonen, Risto, Merikanto, Joonas, O'Donnell, Declan, Paynter, David J., Persad, Geeta G., Rumbold, Steven T., Takemura, Toshihiko, Tsigaridis, Kostas, Undorf, Sabine, Westervelt, Daniel M., Wilcox, Laura J., Allen, Robert J., Samset, Bjørn H., Bollasina, Massimo A., Griffiths, Paul T., Keeble, James, Lund, Marianne T., Makkonen, Risto, Merikanto, Joonas, O'Donnell, Declan, Paynter, David J., Persad, Geeta G., Rumbold, Steven T., Takemura, Toshihiko, Tsigaridis, Kostas, Undorf, Sabine, and Westervelt, Daniel M.
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Changes in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from -0.3 to -1.5 W m-2. Both of these sources of uncertainty are exacerbated on regional scales. The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the
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- 2023
49. Workshop on a future muon program at FNAL
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Corrodi, S., Oksuzian, Y., Edmonds, A., Miller, J., Tran, H. N., Bonventre, R., Brown, D. N., Meot, F., Singh, V., Kolomensky, Y., Tripathy, S., Borrel, L., Bub, M., Echenard, B., Hitlin, D. G., Jafree, H., Middleton, S., Plestid, R., Porter, F. C., Zhu, R. Y., Bottura, L., Pinsard, E., Teixeira, A. M., Carelli, C., Ambrose, D., Badgley, K., Bautista, G. D., Bernstein, R. H., Boi, S., Crnkovic, J., Eldred, J., Gaponenko, A., Johnstone, C., Kiburg, B., Kutschke, R., Lynch, K., Mukherjee, A., Neuffer, D., Pellemoine, F., Pronskikh, V., Rakness, G., Tang, J., Tschirhart, R., Yucel, M., Zettlemoyer, J., Simons, B., Redigolo, D., Diociaiuti, E., Giovannella, S., Miscetti, S., Sarra, I., Muller, S. E., Ootani, W., Yucel, E. B., Kaplan, D. M., Phillips, T. J., Pasternak, J., Palo, D., Davydov, Y., Brown, D., Banerjee, S., Kawall, D., Hartwig, Z., Davidson, S., Abrams, R., Kampa, C., Mackenzie, M., Schmitt, M., Piot, P., Lee, Y. J., Morozov, V., Sato, A., Di Falco, S., Gioiosa, A., Morescalchi, L., Papa, A., Hedges, M. T., Renga, F., Lagrange, J. -B., Rogers, C., Wilcox, D., Petrov, A., Zhao, S., Dukes, E. C., Erlich, R., Group, C., Heeck, J., Pezzullo, G., Nguyen, T., Popp, J. L., Corrodi, S., Oksuzian, Y., Edmonds, A., Miller, J., Tran, H. N., Bonventre, R., Brown, D. N., Meot, F., Singh, V., Kolomensky, Y., Tripathy, S., Borrel, L., Bub, M., Echenard, B., Hitlin, D. G., Jafree, H., Middleton, S., Plestid, R., Porter, F. C., Zhu, R. Y., Bottura, L., Pinsard, E., Teixeira, A. M., Carelli, C., Ambrose, D., Badgley, K., Bautista, G. D., Bernstein, R. H., Boi, S., Crnkovic, J., Eldred, J., Gaponenko, A., Johnstone, C., Kiburg, B., Kutschke, R., Lynch, K., Mukherjee, A., Neuffer, D., Pellemoine, F., Pronskikh, V., Rakness, G., Tang, J., Tschirhart, R., Yucel, M., Zettlemoyer, J., Simons, B., Redigolo, D., Diociaiuti, E., Giovannella, S., Miscetti, S., Sarra, I., Muller, S. E., Ootani, W., Yucel, E. B., Kaplan, D. M., Phillips, T. J., Pasternak, J., Palo, D., Davydov, Y., Brown, D., Banerjee, S., Kawall, D., Hartwig, Z., Davidson, S., Abrams, R., Kampa, C., Mackenzie, M., Schmitt, M., Piot, P., Lee, Y. J., Morozov, V., Sato, A., Di Falco, S., Gioiosa, A., Morescalchi, L., Papa, A., Hedges, M. T., Renga, F., Lagrange, J. -B., Rogers, C., Wilcox, D., Petrov, A., Zhao, S., Dukes, E. C., Erlich, R., Group, C., Heeck, J., Pezzullo, G., Nguyen, T., and Popp, J. L.
- Abstract
The Snowmass report on rare processes and precision measurements recommended Mu2e-II and a next generation muon facility at Fermilab (Advanced Muon Facility) as priorities for the frontier. The Workshop on a future muon program at FNAL was held in March 2023 to discuss design studies for Mu2e-II, organizing efforts for the next generation muon facility, and identify synergies with other efforts (e.g., muon collider). Topics included high-power targetry, status of R&D for Mu2e-II, development of compressor rings, FFA and concepts for muon experiments (conversion, decays, muonium and other opportunities) at AMF. This document summarizes the workshop discussions with a focus on future R&D tasks needed to realize these concepts., Comment: 68 pages, 36 figures
- Published
- 2023
50. Specialty grand challenge : Renaming our section to “Carbon Dioxide Removal”
- Author
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Renforth, Phil, Bellamy, Rob, Beerling, David, Boettcher, Miranda, Bonalumi, Davide, Brandão, Miguel, Fridahl, Mathias, Fuss, Sabine, Hansson, Anders, Heyward, Clare, Kolosz, Ben, Lamers, Patrick, McLaren, Duncan, Pomi, Raffaella, Sanchez, Daniel L., Shayegh, Soheil, Sick, Volker, Van der Spek, Mijndert, Vishal, Vikram, Wilcox, Jennifer, Renforth, Phil, Bellamy, Rob, Beerling, David, Boettcher, Miranda, Bonalumi, Davide, Brandão, Miguel, Fridahl, Mathias, Fuss, Sabine, Hansson, Anders, Heyward, Clare, Kolosz, Ben, Lamers, Patrick, McLaren, Duncan, Pomi, Raffaella, Sanchez, Daniel L., Shayegh, Soheil, Sick, Volker, Van der Spek, Mijndert, Vishal, Vikram, and Wilcox, Jennifer
- Published
- 2023
- Full Text
- View/download PDF
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