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1. Chronic glycemic control influences the relationship between acute perioperative dysglycemia and perioperative outcome

Author: Brandon Stretton, Andrew E. C. Booth, Joshua Kovoor, Aashray Gupta, Ammar Zaka, Suzanne Edwards, S. George Barreto, Guy Maddern, Stephen Bacchi, and Mark Boyd
Subjects: glycemic control, perioperative, stress hyperglycemia ratio, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract: Abstract Background The objective of this study was to evaluate the impact of dysglycemia on perioperative outcomes, in patients with and without diabetes, and how prior glycemic control modifies these relationships. Methods Consecutive surgical patients admitted to six South Australian tertiary hospitals between 2017 and 2023 were included. Blood glucose levels within 48 h pre‐ and post‐operatively were assessed in an adjusted analyses against a priori selected covariates. Dysglycemia metrics were hyperglycemia (>10.0 mmol/L), hypoglycemia (1.7 mmol/L), and stress hyperglycemic ratio (SHR). The primary outcome was hospital mortality. Results Of 52 145 patients, 7490 (14.4%) had recognized diabetes. Inpatient mortality was observed in 787 patients (1.5%), of which 150 (19.1%) had diabetes mellitus. Hyperglycemia was associated with increased mortality in patients with diabetes (odds ratio [OR] = 2.99, 95% CI: 1.63–5.67, p = 0.004) but not in non‐diabetics, who instead had an increased odds of intensive care unit (ICU) admission if hyperglycemic (OR = 1.95, 95% CI: 1.40–2.72, p
Published: 2024
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2. SurvNet: A low-complexity convolutional neural network for survival time classification of patients with glioblastoma

Author: Qiyuan Lyu, Mario Parreno-Centeno, João Paulo Papa, Esin Öztürk-Isik, Thomas C. Booth, and Fumie Costen
Subjects: Brain tumor glioma glioblastoma, Overall survival classification deep learning, Magnetic resonance imaging convolutional neural network, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: Background and objective: Malignant primary brain tumors cause the greatest number of years of life lost than any other cancer. Grade 4 glioma is particularly devastating: The median survival without any treatment is less than six months and with standard-of-care treatment is only 14.6 months. Accurate identification of the overall survival time of patients with brain tumors is of profound importance in many clinical applications. Automated image analytics with magnetic resonance imaging (MRI) can provide insights into the prognosis of patients with brain tumors. Methods: In this paper, We propose SurvNet, a low-complexity deep learning architecture based on the convolutional neural network to classify the overall survival time of patients with brain tumors into long-time and short-time survival cohorts. Through the incorporation of diverse MRI modalities as inputs, we facilitate deep feature extraction at various anatomical sites, thereby augmenting the precision of predictive modeling. We compare SurvNet with the Inception V3, VGG 16 and ensemble CNN models on pre-operative magnetic resonance image datasets. We also analyzed the effect of segmented brain tumors and training data on the system performance. Results: Several measures, such as accuracy, precision, and recall, are calculated to examine the perfor-mance of SurvNet on three-fold cross-validation. SurvNet with T1 MRI modality achieved a 62.7 % accuracy, compared with 52.9 % accuracy of the Inception V3 model, 58.5 % accuracy of the VGG 16 model, and 54.9 % of the ensemble CNN model. By increasing the MRI input modalities, SurvNet becomes more accurate and achieves 76.5 % accuracy with four MRI modalities. Combining the segmented data, SurvNet achieved the highest accuracy of 82.4 %. Conclusions: The research results show that SurvNet achieves higher metrics such as accuracy and f1-score than the comparisons. Our research also proves that by using multiparametric MRI modalities, SurvNet is able to learn more image features and performs a better classification accuracy. We can conclude that SurvNet with the complete scenario, i.e., segmented data and four MRI modalities, achieved the best accuracy, showing the validity of segmentation information during the survival time prediction process.
Published: 2024
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3. Constraint Programming Models for Depth-Optimal Qubit Assignment and SWAP-Based Routing (Short Paper).

Author: Kyle E. C. Booth
Published: 2023
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4. Splanchnic sympathetic nerve denervation improves bacterial clearance and clinical recovery in established ovine Gram-negative bacteremia

Author: Rachel M. Peiris, Clive N. May, Lindsea C. Booth, Robin M. McAllen, Michael J. McKinley, Sally Hood, Davide Martelli, Rinaldo Bellomo, and Yugeesh R. Lankadeva
Subjects: Bacteremia, Sepsis, Splanchnic sympathetic nerves, Cytokines, Inflammation, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract: Abstract Background The autonomic nervous system can modulate the innate immune responses to bacterial infections via the splanchnic sympathetic nerves. Here, we aimed to determine the effects of bilateral splanchnic sympathetic nerve denervation on blood pressure, plasma cytokines, blood bacterial counts and the clinical state in sheep with established bacteremia. Methods Conscious Merino ewes received an intravenous infusion of Escherichia coli for 30 h (1 × 109 colony forming units/mL/h) to induce bacteremia. At 24 h, sheep were randomized to have bilaterally surgically implanted snares pulled to induce splanchnic denervation (N = 10), or not pulled (sham; N = 9). Results Splanchnic denervation did not affect mean arterial pressure (84 ± 3 vs. 84 ± 4 mmHg, mean ± SEM; PGroup = 0.7) compared with sham treatment at 30-h of bacteremia. Splanchnic denervation increased the plasma levels of the pro-inflammatory cytokine interleukin-6 (9.2 ± 2.5 vs. 3.8 ± 0.3 ng/mL, PGroup = 0.031) at 25-h and reduced blood bacterial counts (2.31 ± 0.45 vs. 3.45 ± 0.11 log10 [CFU/mL + 1], PGroup = 0.027) at 26-h compared with sham treatment. Plasma interleukin-6 and blood bacterial counts returned to sham levels by 30-h. There were no differences in the number of bacteria present within the liver (PGroup = 0.3). However, there was a sustained improvement in clinical status, characterized by reduced respiratory rate (PGroup = 0.024) and increased cumulative water consumption (PGroup = 0.008) in splanchnic denervation compared with sham treatment. Conclusion In experimental Gram-negative bacteremia, interrupting splanchnic sympathetic nerve activity increased plasma interleukin-6, accelerated bacterial clearance, and improved clinical state without inducing hypotension. These findings suggest that splanchnic neural manipulation is a potential target for pharmacological or non-pharmacological interventions.
Published: 2023
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5. Editorial: Rising stars in neuroradiology: 2022

Author: Thomas C. Booth
Subjects: deep learning, flow diverter, stroke, T2 relaxometry, NODDI, 18F-synvest-1, Medical physics. Medical radiology. Nuclear medicine, R895-920
Published: 2024
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6. Factors affecting the labelling accuracy of brain MRI studies relevant for deep learning abnormality detection

Author: Matthew Benger, David A. Wood, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Jeremy Lynch, Matthew Townend, Antanas Montvila, Juveria Siddiqui, Naveen Gadapa, Gareth Barker, Sebastian Ourselin, James H. Cole, and Thomas C. Booth
Subjects: deep learning, computer vision system, labelling, neuroradiology, MRI, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract: Unlocking the vast potential of deep learning-based computer vision classification systems necessitates large data sets for model training. Natural Language Processing (NLP)—involving automation of dataset labelling—represents a potential avenue to achieve this. However, many aspects of NLP for dataset labelling remain unvalidated. Expert radiologists manually labelled over 5,000 MRI head reports in order to develop a deep learning-based neuroradiology NLP report classifier. Our results demonstrate that binary labels (normal vs. abnormal) showed high rates of accuracy, even when only two MRI sequences (T2-weighted and those based on diffusion weighted imaging) were employed as opposed to all sequences in an examination. Meanwhile, the accuracy of more specific labelling for multiple disease categories was variable and dependent on the category. Finally, resultant model performance was shown to be dependent on the expertise of the original labeller, with worse performance seen with non-expert vs. expert labellers.
Published: 2023
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7. Federated learning enables big data for rare cancer boundary detection

Author: Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña Quintero, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, Joseph Lombardo, Joshua D. Palmer, Adam E. Flanders, Adam P. Dicker, Haris I. Sair, Craig K. Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y. So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A. Vogelbaum, J. Ross Mitchell, Joaquim Farinhas, Joseph A. Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C. Pinho, Divya Reddy, James Holcomb, Benjamin C. Wagner, Benjamin M. Ellingson, Timothy F. Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B. Martins, Bernardo C. A. Teixeira, Flávia Sprenger, David Menotti, Diego R. Lucio, Pamela LaMontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W. Lui, Richard McKinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E. Sloan, Vachan Vadmal, Kristin Waite, Rivka R. Colen, Linmin Pei, Murat Ak, Ashok Srinivasan, J. Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V. M. Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I. Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M. Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R. van der Voort, Ahmed Alafandi, Fatih Incekara, Maarten M. J. Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W. Schouten, Hendrikus J. Dubbink, Arnaud J. P. E. Vincent, Martin J. van den Bent, Pim J. French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P. Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B. Chambless, Akshitkumar Mistry, Reid C. Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C. Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G. H. Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M. Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F. Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M. Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A. Velastin, Godwin Ogbole, Mayowa Soneye, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu’aibu, Adeleye Dorcas, Farouk Dako, Amber L. Simpson, Mohammad Hamghalam, Jacob J. Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y. Moraes, Michael A. Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S. Barnholtz-Sloan, Jason Martin, and Spyridon Bakas
Subjects: Science
Abstract: Federated ML (FL) provides an alternative to train accurate and generalizable ML models, by only sharing numerical model updates. Here, the authors present the largest FL study to-date to generate an automatic tumor boundary detector for glioblastoma.
Published: 2022
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8. Suicidal chemotaxis in bacteria

Author: Nuno M. Oliveira, James H. R. Wheeler, Cyril Deroy, Sean C. Booth, Edmond J. Walsh, William M. Durham, and Kevin R. Foster
Subjects: Science
Abstract: Bacteria respond to nutrients and other compounds via chemotaxis, but little is known of their responses to antibiotics. By tracking cells in antibiotic gradients, the authors show that surface-attached Pseudomonas aeruginosa move towards antibiotics in what appears to be a suicidal attack strategy.
Published: 2022
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9. Artificial intelligence in the autonomous navigation of endovascular interventions: a systematic review

Author: Harry Robertshaw, Lennart Karstensen, Benjamin Jackson, Hadi Sadati, Kawal Rhode, Sebastien Ourselin, Alejandro Granados, and Thomas C. Booth
Subjects: artificial intelligence, machine learning, endovascular intervention, autonomy, navigation, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: BackgroundAutonomous navigation of catheters and guidewires in endovascular interventional surgery can decrease operation times, improve decision-making during surgery, and reduce operator radiation exposure while increasing access to treatment.ObjectiveTo determine from recent literature, through a systematic review, the impact, challenges, and opportunities artificial intelligence (AI) has for the autonomous navigation of catheters and guidewires for endovascular interventions.MethodsPubMed and IEEEXplore databases were searched to identify reports of AI applied to autonomous navigation methods in endovascular interventional surgery. Eligibility criteria included studies investigating the use of AI in enabling the autonomous navigation of catheters/guidewires in endovascular interventions. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), articles were assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). PROSPERO: CRD42023392259.ResultsFour hundred and sixty-two studies fulfilled the search criteria, of which 14 studies were included for analysis. Reinforcement learning (RL) (9/14, 64%) and learning from expert demonstration (7/14, 50%) were used as data-driven models for autonomous navigation. These studies evaluated models on physical phantoms (10/14, 71%) and in-silico (4/14, 29%) models. Experiments within or around the blood vessels of the heart were reported by the majority of studies (10/14, 71%), while non-anatomical vessel platforms “idealized” for simple navigation were used in three studies (3/14, 21%), and the porcine liver venous system in one study. We observed that risk of bias and poor generalizability were present across studies. No procedures were performed on patients in any of the studies reviewed. Moreover, all studies were limited due to the lack of patient selection criteria, reference standards, and reproducibility, which resulted in a low level of evidence for clinical translation.ConclusionDespite the potential benefits of AI applied to autonomous navigation of endovascular interventions, the field is in an experimental proof-of-concept stage, with a technology readiness level of 3. We highlight that reference standards with well-identified performance metrics are crucial to allow for comparisons of data-driven algorithms proposed in the years to come.Systematic review registrationidentifier: CRD42023392259.
Published: 2023
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10. More vaquita porpoises survive than expected

Author: L Rojas-Bracho, B Taylor, C Booth, L Thomas, A Jaramillo-Legorreta, E Nieto-García, G Cárdenas Hinojosa, J Barlow, SL Mesnick, T Gerrodette, P Olson, A Henry, H Rizo, E Hidalgo-Pla, and A Bonilla-Garzón
Subjects: Zoology, QL1-991, Botany, QK1-989
Abstract: In 2018, it was estimated that fewer than 20 of Mexico’s endemic vaquita porpoise Phocoena sinus remained, and the species was declining by 47% yr-1. Entanglement in gillnets is the sole threat to the species, and since the last population size estimate, gillnetting has increased in the small area where most vaquitas remain—a 12 × 24 km area in the Gulf of California near San Felipe, Mexico. We conducted research efforts in 2019 and 2021 in that area to estimate the minimum numbers of adults and calves and look for any signs that vaquitas are unhealthy. Through expert elicitation, we estimated between 7 and 15 unique individuals were seen in 2019 and 5-13 were seen in 2021. Calves were seen in both years, and all vaquitas appeared healthy. Population projections from the last full survey indicated that more vaquitas have survived than expected. We suggest that these surviving adult vaquitas may have learned to avoid entanglement in gillnets. These vaquitas and their calves provide hope that the species can survive. However, given the high levels of illegal gillnetting and the theft of equipment which hindered our monitoring efforts, and with only around 10 individuals remaining, survival can only be assured if vaquita habitat is made gillnet-free.
Published: 2022
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11. Automated triaging of head MRI examinations using convolutional neural networks.

Author: David A. Wood 0004, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Antanas Montvila, Siddharth Agarwal, Jeremy Lynch, Matthew Townend, Gareth J. Barker, Sébastien Ourselin, James H. Cole, and Thomas C. Booth
Published: 2021

12. Cultivation and Fertility Practices Influence Hybrid Bermudagrass Recovery from Spring Dead Spot Damage

Author: Wendell J. Hutchens, Jordan C. Booth, J. Michael Goatley, and David S. McCall
Subjects: aerification, disease, nitrogen, ophiosphaerella, turf, urea, vertical mowing, Plant culture, SB1-1110
Abstract: Spring dead spot (SDS), caused by Ophiosphaerella spp., is among the most damaging diseases to hybrid bermudagrass (Cynodon dactylon × transvaalensis) in areas where winter dormancy occurs. Management strategies that aid in turfgrass recovery from SDS damage have not been widely studied. An experiment was conducted in Blacksburg, VA, in 2019 and 2020, to determine the influence of various cultural practices on bermudagrass recovery from SDS damage. Fertility and cultivation were applied in the late spring/early summer, which is earlier than normal for cultivation practices for bermudagrass, to test their effectiveness in aiding bermudagrass recovery from SDS damage. The main effects of fertility and cultivation were arranged in a 2 × 3 factorial design with vertical mowing, solid-tine aerification, and no cultivation applied with urea (48.8 kg⋅ha−1 N) sprayed at trial initiation and 2 weeks later or without urea. Plots were assessed for the percent of SDS throughout the study. Data were analyzed as the percent change relative to the initial assessment to measure bermudagrass recovery. The main effect of fertility increased bermudagrass recovery from SDS damage in both 2019 and 2020. The main effects of vertical mowing and solid-tine aerification reduced bermudagrass recovery from SDS damage in 2020. These data suggest that two properly timed nitrogen fertilization applications at 48.8 kg⋅ha−1 optimized bermudagrass recovery from SDS damage, whereas late spring/early summer cultivation without fertility may inhibit bermudagrass recovery.
Published: 2022
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13. Imaging Timing After Surgery for Glioblastoma (INTERVAL GB): A multi-centre, UK and Ireland retrospective cohort study

Author: Emily Rose Bligh, Conor Gillespie, Michael T.C. Poon, Georgios Solomou, Melissa Gough, Abdurrahman I. Islim, Christopher P. Millward, Ola Rominiyi, Rasheed Zakaria, Stephen J. Price, Colin Watts, Sophie Camp, Thomas C. Booth, Gerard Thompson, Samantha J. Mills, Adam Waldman, Paul Brennan, and Michael D. Jenkinson
Subjects: Neurology. Diseases of the nervous system, RC346-429
Published: 2023
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14. Integer Programming Techniques for Minor-Embedding in Quantum Annealers.

Author: David E. Bernal, Kyle E. C. Booth, Raouf Dridi, Hedayat Alghassi, Sridhar R. Tayur, and Davide Venturelli
Published: 2020
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15. Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM).

Author: David A. Wood 0004, Jeremy Lynch, Sina Kafiabadi, Emily Guilhem, Aisha Al Busaidi, Antanas Montvila, Thomas Varsavsky, Juveria Siddiqui, Naveen Gadapa, Matthew Townend, Martin Kiik, Keena Patel, Gareth J. Barker, Sébastien Ourselin, James H. Cole, and Thomas C. Booth
Published: 2020

16. Machine Learning and Glioblastoma: Treatment Response Monitoring Biomarkers in 2021.

Author: Thomas C. Booth, Bernice Akpinar, Andrei Roman, Haris Shuaib, Aysha Luis, Alysha Chelliah, Ayisha Al Busaidi, Ayesha Mirchandani, Burcu Alparslan, Nina Mansoor, Keyoumars Ashkan, Sébastien Ourselin, and Marc Modat
Published: 2020
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17. Labelling Imaging Datasets on the Basis of Neuroradiology Reports: A Validation Study.

Author: David A. Wood 0004, Sina Kafiabadi, Aisha Al Busaidi, Emily Guilhem, Jeremy Lynch, Matthew Townend, Antanas Montvila, Juveria Siddiqui, Naveen Gadapa, Matthew Benger, Gareth J. Barker, Sébastien Ourselin, James H. Cole, and Thomas C. Booth
Published: 2020
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18. Quantum-Accelerated Global Constraint Filtering.

Author: Kyle E. C. Booth, Bryan O'Gorman, Jeffrey Marshall, Stuart Hadfield, and Eleanor Gilbert Rieffel
Published: 2020
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19. Imaging timing after glioblastoma surgery (INTERVAL-GB): protocol for a UK and Ireland, multicentre retrospective cohort study

Author: Oliver Burton, Julie Woodfield, Daniel Richardson, Giles Critchley, Angelos Kolias, Thomas Santarius, Lewis Thorne, Peter Whitfield, Ola Rominiyi, Bharti Kewlani, Harsh Bhatt, Ahmed Ahmed, Michael O’Sullivan, Rasheed Zakaria, Michael D Jenkinson, Gerard Thompson, Paul M Brennan, Rory Piper, Seong Hoon Lee, Neil Barua, Engelbert Mthunzi, Sara Venturini, Daniel M Fountain, Najma Ahmed, Stephen J Price, Colin Watts, Michael T C Poon, Stuart Smith, Anand Pandit, Ryan K Mathew, Soham Bandyopadhyay, Rosa Sun, Setthasorn Zhi Yang Ooi, Victoria Wykes, William Bolton, Abdullah Egiz, Samantha J Mills, Babar Vaqas, Natalie Simon, Puneet Plaha, Georgios Solomou, Aswin Chari, Grainne McKenna, Melissa Gough, Simon Lammy, Sophie T Williams, Isabelle Williams, Andrew J Martin, Sam Hodgson, Robert Spencer, Adam Waldman, Armin Nazari, Joshua Erhabor, Omar Salim, Saad Moughal, Chinedu Brian Egu, Abdurrahman I Islim, Christopher P Millward, Suhaib Abualsaud, Michael Amoo, Neeraj Kalra, Agbolahan Sofela, Thomas C Booth, George E Richardson, Conor S Gillespie, Orla Mantle, Abigail Clynch, Jay J Park, Emily R Bligh, Avani Shanbhag, Moritz Steinruecke, Alvaro Yanez Touzet, Hannah Redpath, Gideon Adegboyega, Prithvi Bahu, Rosaline de Koning, Tomas Ferreira, Dana Hutton, Jashan Selvakumar, Tiffany TS Ye, Ashvin Kuri, Robin Borchert, Bea Duric, Elena Roman, Kristy Kehoe, Jeremy Cheong, Lauren Harris, Mohammad A Mustafa, Hidayatul Abdullmalek, Chinelo Afulukwe, Abdelsalam Nedal Al-Sousi, Yahia Al-Tamimi, Ajitesh Anand, Peter Bodkin, Ion Boiangiu, Abbey Boyle, Christiaan Bredell, Talhah Chaudri, Ana Cios, Iona Cleer, David Coope, Ian Coulter, Harriet Davis, Paolo Jose De Luna, Nayan Dey, Justyna O Ekert, Jinendra Ekanayake, Anna Elso, Tom Flannery, Kwan Wai Fung, Rahul Ganguly, Sanay Goyal, Emily Hardman, Theodore Hirst, Kelvin Sunn Hoah, Kismet Hossain-Ibrahim, Lena Mary Houlihan, Sami Squali Houssaini, Sadid Hoque, Mahnoor Javed, Siddarth Kannan, Efthymia Maria Kapasouri, Andrew Keenlyside, Prerna Khanna, Kunalika Sathish Kumar, Eunkyung Lee, Robert Magouirk, Riccardo Masina, Adele Mazzoleni, Patrick McAleavey, Daniel McSweeney, Trinh Ton Nu Ngoc, Shiva A Nischal, Jonathan Pesic-Smith, Peter Peterson, Isaac Phang, Shyam Pujara, Marwa Mohammed Elrasheed Saad, Shinjan Sangal, Veekshith Shetty, Irtiza Syed, Jesvin Tom Sunny, Anca-Mihaela Vasilica, Daniel O’Flaherty, Arslan Khaliq Raja, Daniele Ramsay, Renitha Reddi, Dorina Roy, Jeremiah Samkutty, Edward Jerome St George, Preethi Subramanian, Vaibhav Sundaresan, Kieron Sweeney, Boon Hoe Tan, Nicole Turnbull, Yuewei Tao, Rebecca Tweedie, Anastasia Tzatzidou, Kathrin Whitehouse, Jack Wildman, Karl Williams, Kelvin Sunn Yap, Mahir Yousuff, Asaad Zulfiqar, Sophie Camp, and Setthasorn ZY Ooi
Subjects: Medicine
Abstract: Introduction Glioblastoma is the most common malignant primary brain tumour with a median overall survival of 12–15 months (range 6–17 months), even with maximal treatment involving debulking neurosurgery and adjuvant concomitant chemoradiotherapy. The use of postoperative imaging to detect progression is of high importance to clinicians and patients, but currently, the optimal follow-up schedule is yet to be defined. It is also unclear how adhering to National Institute for Health and Care Excellence (NICE) guidelines—which are based on general consensus rather than evidence—affects patient outcomes such as progression-free and overall survival. The primary aim of this study is to assess MRI monitoring practice after surgery for glioblastoma, and to evaluate its association with patient outcomes.Methods and analysis ImagiNg Timing aftER surgery for glioblastoma: an eVALuation of practice in Great Britain and Ireland is a retrospective multicentre study that will include 450 patients with an operated glioblastoma, treated with any adjuvant therapy regimen in the UK and Ireland. Adult patients ≥18 years diagnosed with glioblastoma and undergoing surgery between 1 August 2018 and 1 February 2019 will be included. Clinical and radiological scanning data will be collected until the date of death or date of last known follow-up. Anonymised data will be uploaded to an online Castor database. Adherence to NICE guidelines and the effect of being concordant with NICE guidelines will be identified using descriptive statistics and Kaplan-Meier survival analysis.Ethics and dissemination Each participating centre is required to gain local institutional approval for data collection and sharing. Formal ethical approval is not required since this is a service evaluation. Results of the study will be reported through peer-reviewed presentations and articles, and will be disseminated to participating centres, patients and the public.
Published: 2022
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20. The changing landscape of cerebral revascularization surgery: A United Kingdom experience

Author: Mathew J. Gallagher, Joseph Frantzias, Ahilan Kailaya-Vasan, Thomas C. Booth, and Christos M. Tolias
Subjects: cerebral bypass surgery, cerebral bypass, cerebral revascularisation, cerebral revascularization surgery, flow diversion, flow diverting stent, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract: ObjectiveWe describe the chronological trends in cerebral revascularization surgery through a single-surgeon experience; and we review whether in the context of giant and fusiform cerebral aneurysms, flow-diverting stents have impacted on the use of cerebral revascularization surgery.MethodsWe review our single institution prospectively collected database of cerebral revascularization procedures between 2006 and 2018. Comparing this to our database of flow-diverting endovascular stent procedures, we compare the treatment of fusiform and giant aneurysms. We describe patient demographics, procedural incidence, complications, and outcomes.ResultsBetween 2006 and 2018, 50 cerebral revascularization procedures were performed. The incidence of cerebral revascularization surgery is declining. In the context of giant/fusiform aneurysm treatment, the decline in cerebral revascularization is accompanied by a rise in the use of flow-diverting endovascular stents. Thirty cerebral revascularizations were performed for moyamoya disease and 11 for giant/fusiform aneurysm. Four (14%) direct bypass grafts occluded without neurological sequela. Other morbidity included hydrocephalus (2%), transient ischemic attacks (2%), and ischemic stroke (2%). There was one procedure-related mortality (2%). Flow-diverting stents were inserted for seven fusiform and seven giant aneurysms. Comparing the treatment of giant/fusiform aneurysms, there was no significant difference in morbidity and mortality between cerebral revascularization and flow-diverting endovascular stents.ConclusionWe conclude that with the decline in the incidence of cerebral revascularization surgery, there is a need for centralization of services to allow high standards and outcomes to be maintained.
Published: 2022
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21. Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study

Author: Mohammad A. Dabbah, Angus B. Reed, Adam T. C. Booth, Arrash Yassaee, Aleksa Despotovic, Benjamin Klasmer, Emily Binning, Mert Aral, David Plans, Davide Morelli, Alain B. Labrique, and Diwakar Mohan
Subjects: Medicine, Science
Abstract: Abstract The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.
Published: 2021
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22. Blunted natriuretic response to saline loading in sheep with hypertensive kidney disease following radiofrequency catheter-based renal denervation

Author: Reetu R. Singh, Zoe McArdle, Harshil Singh, Lindsea C. Booth, Clive N. May, Geoffrey A. Head, Karen M. Moritz, Markus P. Schlaich, and Kate M. Denton
Subjects: Medicine, Science
Abstract: Abstract Renal sympathetic nerves contribute to renal excretory function during volume expansion. We hypothesized that intact renal innervation is required for excretion of a fluid/electrolyte load in hypertensive chronic kidney disease (CKD) and normotensive healthy settings. Blood pressure, kidney hemodynamic and excretory response to 180 min of isotonic saline loading (0.13 ml/kg/min) were examined in female normotensive (control) and hypertensive CKD sheep at 2 and 11 months after sham (control-intact, CKD-intact) or radiofrequency catheter-based RDN (control-RDN, CKD-RDN) procedure. Basal blood pressure was ~ 7 to 9 mmHg lower at 2, and 11 months in CKD-RDN compared with CKD-intact sheep. Saline loading did not alter glomerular filtration rate in any group. At 2 months, in response to saline loading, total urine and sodium excretion were ~ 40 to 50% less, in control-RDN and CKD-RDN than intact groups. At 11 months, the natriuretic and diuretic response to saline loading were similar between control-intact, control-RDN and CKD-intact groups but sodium excretion was ~ 42% less in CKD-RDN compared with CKD-intact at this time-point. These findings indicate that chronic withdrawal of basal renal sympathetic activity impairs fluid/electrolyte excretion during volume expansion. Clinically, a reduced ability to excrete a saline load following RDN may contribute to disturbances in body fluid balance in hypertensive CKD.
Published: 2021
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23. Author Correction: Federated learning enables big data for rare cancer boundary detection

Author: Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, Joseph Lombardo, Joshua D. Palmer, Adam E. Flanders, Adam P. Dicker, Haris I. Sair, Craig K. Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y. So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A. Vogelbaum, J. Ross Mitchell, Joaquim Farinhas, Joseph A. Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C. Pinho, Divya Reddy, James Holcomb, Benjamin C. Wagner, Benjamin M. Ellingson, Timothy F. Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B. Martins, Bernardo C. A. Teixeira, Flávia Sprenger, David Menotti, Diego R. Lucio, Pamela LaMontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W. Lui, Richard McKinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E. Sloan, Vachan Vadmal, Kristin Waite, Rivka R. Colen, Linmin Pei, Murat Ak, Ashok Srinivasan, J. Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V. M. Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I. Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M. Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R. van der Voort, Ahmed Alafandi, Fatih Incekara, Maarten M. J. Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W. Schouten, Hendrikus J. Dubbink, Arnaud J. P. E. Vincent, Martin J. van den Bent, Pim J. French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P. Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B. Chambless, Akshitkumar Mistry, Reid C. Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C. Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G. H. Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M. Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F. Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M. Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A. Velastin, Godwin Ogbole, Mayowa Soneye, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu’aibu, Adeleye Dorcas, Farouk Dako, Amber L. Simpson, Mohammad Hamghalam, Jacob J. Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y. Moraes, Michael A. Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S. Barnholtz-Sloan, Jason Martin, and Spyridon Bakas
Subjects: Science
Published: 2023
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24. Gene Edited T Cell Therapies for Inborn Errors of Immunity

Author: T. A. Fox, B. C. Houghton, and C. Booth
Subjects: primary immumunodeficiencies, inborn error of immunity (IEI), gene editing, t cell, cellular therapeutics, gene therapeutics, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract: Inborn errors of immunity (IEIs) are a heterogeneous group of inherited disorders of the immune system. Many IEIs have a severe clinical phenotype that results in progressive morbidity and premature mortality. Over 450 IEIs have been described and the incidence of all IEIs is 1/1,000–10,000 people. Current treatment options are unsatisfactory for many IEIs. Allogeneic haematopoietic stem cell transplantation (alloHSCT) is curative but requires the availability of a suitable donor and carries a risk of graft failure, graft rejection and graft-versus-host disease (GvHD). Autologous gene therapy (GT) offers a cure whilst abrogating the immunological complications of alloHSCT. Gene editing (GE) technologies allow the precise modification of an organisms’ DNA at a base-pair level. In the context of genetic disease, this enables correction of genetic defects whilst preserving the endogenous gene control machinery. Gene editing technologies have the potential to transform the treatment landscape of IEIs. In contrast to gene addition techniques, gene editing using the CRISPR system repairs or replaces the mutation in the DNA. Many IEIs are limited to the lymphoid compartment and may be amenable to T cell correction alone (rather than haematopoietic stem cells). T cell Gene editing has the advantages of higher editing efficiencies, reduced risk of deleterious off-target edits in terminally differentiated cells and less toxic conditioning required for engraftment of lymphocytes. Although most T cells lack the self-renewing property of HSCs, a population of T cells, the T stem cell memory compartment has long-term multipotent and self-renewal capacity. Gene edited T cell therapies for IEIs are currently in development and may offer a less-toxic curative therapy to patients affected by certain IEIs. In this review, we discuss the history of T cell gene therapy, developments in T cell gene editing cellular therapies before detailing exciting pre-clinical studies that demonstrate gene editing T cell therapies as a proof-of-concept for several IEIs.
Published: 2022
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25. Supernova neutrino burst detection with the deep underground neutrino experiment

Author: B. Abi, R. Acciarri, M. A. Acero, G. Adamov, D. Adams, M. Adinolfi, Z. Ahmad, J. Ahmed, T. Alion, S. Alonso Monsalve, C. Alt, J. Anderson, C. Andreopoulos, M. P. Andrews, F. Andrianala, S. Andringa, A. Ankowski, M. Antonova, S. Antusch, A. Aranda-Fernandez, A. Ariga, L. O. Arnold, M. A. Arroyave, J. Asaadi, A. Aurisano, V. Aushev, D. Autiero, F. Azfar, H. Back, J. J. Back, C. Backhouse, P. Baesso, L. Bagby, R. Bajou, S. Balasubramanian, P. Baldi, B. Bambah, F. Barao, G. Barenboim, G. J. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, N. Barros, J. L. Barrow, A. Bashyal, V. Basque, F. Bay, J. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, D. Belver, N. Benekos, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, H. Berns, S. Bertolucci, M. Betancourt, Y. Bezawada, M. Bhattacharjee, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, B. Blanco Siffert, F. D. M. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, M. Bonesini, M. Bongrand, F. Bonini, A. Booth, C. Booth, S. Bordoni, A. Borkum, T. Boschi, N. Bostan, P. Bour, S. B. Boyd, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Brandt, J. Bremer, C. Brew, E. Brianne, S. J. Brice, C. Brizzolari, C. Bromberg, G. Brooijmans, J. Brooke, A. Bross, G. Brunetti, N. Buchanan, H. Budd, D. Caiulo, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, L. Camilleri, A. Caminata, M. Campanelli, D. Caratelli, G. Carini, B. Carlus, P. Carniti, I. Caro Terrazas, H. Carranza, A. Castillo, C. Castromonte, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, C. Chang, E. Chardonnet, A. Chatterjee, S. Chattopadhyay, J. Chaves, H. Chen, M. Chen, Y. Chen, D. Cherdack, C. Chi, S. Childress, A. Chiriacescu, K. Cho, S. Choubey, A. Christensen, D. Christian, G. Christodoulou, E. Church, P. Clarke, T. E. Coan, A. G. Cocco, J. A. B. Coelho, E. Conley, J. M. Conrad, M. Convery, L. Corwin, P. Cotte, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, E. Cristaldo, R. Cross, C. Cuesta, Y. Cui, D. Cussans, M. Dabrowski, H. da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, R. M. De Almeida, P. Debbins, I. De Bonis, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell-Acqua, P. De Lurgio, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. Deptuch, A. De Roeck, V. De Romeri, J. J. De Vries, R. Dharmapalan, M. Dias, F. Diaz, J. S. Díaz, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, N. Dokania, M. J. Dolinski, L. Domine, D. Douglas, F. Drielsma, D. Duchesneau, K. Duffy, P. Dunne, T. Durkin, H. Duyang, O. Dvornikov, D. A. Dwyer, A. S. Dyshkant, M. Eads, D. Edmunds, J. Eisch, S. Emery, A. Ereditato, C. O. Escobar, L. Escudero Sanchez, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, C. Farnese, Y. Farzan, J. Felix, E. Fernandez-Martinez, P. Fernandez Menendez, F. Ferraro, L. Fields, A. Filkins, F. Filthaut, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, S. Fuess, I. Furic, A. P. Furmanski, A. Gago, H. Gallagher, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, R. Gandhi, R. Gandrajula, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, G. Ge, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, D. Gibin, I. Gil-Botella, C. Girerd, A. K. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. V. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, J. A. Gonzalez-Cuevas, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, M. Graham, E. Gramellini, R. Gran, E. Granados, A. Grant, C. Grant, D. Gratieri, P. Green, S. Green, L. Greenler, M. Greenwood, J. Greer, W. C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, V. Guarino, R. Guenette, A. Guglielmi, B. Guo, K. K. Guthikonda, R. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, A. Hackenburg, H. Hadavand, R. Haenni, A. Hahn, J. Haigh, J. Haiston, T. Hamernik, P. Hamilton, J. Han, K. Harder, D. A. Harris, J. Hartnell, T. Hasegawa, R. Hatcher, E. Hazen, A. Heavey, K. M. Heeger, J. Heise, K. Hennessy, S. Henry, M. A. Hernandez Morquecho, K. Herner, L. Hertel, A. S. Hesam, J. Hewes, A. Higuera, T. Hill, S. J. Hillier, A. Himmel, J. Hoff, C. Hohl, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, J. Huang, J. Hugon, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, A. Ioannisian, R. Itay, A. Izmaylov, E. James, B. Jargowsky, F. Jediny, C. Jesùs-Valls, X. Ji, L. Jiang, S. Jiménez, A. Jipa, A. Joglekar, C. Johnson, R. Johnson, B. Jones, S. Jones, C. K. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, F. Kamiya, G. Karagiorgi, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, K. Koehler, L. W. Koerner, S. Kohn, P. P. Koller, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, F. Krennrich, I. Kreslo, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, R. Kumar, C. Kuruppu, V. Kus, T. Kutter, A. Lambert, K. Lande, C. E. Lane, K. Lang, T. Langford, P. Lasorak, D. Last, C. Lastoria, A. Laundrie, A. Lawrence, I. Lazanu, R. LaZur, T. Le, J. Learned, P. LeBrun, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, M. Leyton, L. Li, S. Li, S. W. Li, T. Li, Y. Li, H. Liao, C. S. Lin, S. Lin, A. Lister, B. R. Littlejohn, J. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, K. Loo, D. Lorca, T. Lord, J. M. LoSecco, W. C. Louis, K. B. Luk, X. Luo, N. Lurkin, T. Lux, V. P. Luzio, D. MacFarland, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, A. Maddalena, P. Madigan, S. Magill, K. Mahn, A. Maio, A. Major, J. A. Maloney, G. Mandrioli, J. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, F. Marinho, A. D. Marino, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martin-Albo, N. Martinez, D. A. Martinez Caicedo, S. Martynenko, K. Mason, A. Mastbaum, M. Masud, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, R. Mazza, A. Mazzacane, E. Mazzucato, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, M. Mellinato, O. Mena, S. Menary, H. Mendez, A. Menegolli, G. Meng, M. D. Messier, W. Metcalf, M. Mewes, H. Meyer, T. Miao, G. Michna, T. Miedema, J. Migenda, R. Milincic, W. Miller, J. Mills, C. Milne, O. Mineev, O. G. Miranda, S. Miryala, C. S. Mishra, S. R. Mishra, A. Mislivec, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, A. Montanari, C. Montanari, D. Montanari, L. M. Montano Zetina, J. Moon, M. Mooney, A. Moor, D. Moreno, B. Morgan, C. Morris, C. Mossey, E. Motuk, C. A. Moura, J. Mousseau, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, D. Navas-Nicolás, N. Nayak, M. Nebot-Guinot, L. Necib, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, D. Newhart, R. Nichol, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, A. Olivares Del Campo, A. Olivier, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, S. Pakvasa, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. J. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. M. Peeters, Y. Penichot, E. Pennacchio, A. Penzo, O. L. G. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, F. Piastra, L. Pickering, F. Pietropaolo, J. Pillow, J. Pinzino, R. Plunkett, R. Poling, X. Pons, N. Poonthottathil, S. Pordes, M. Potekhin, R. Potenza, B. V. K. S. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, S. Prince, G. Prior, D. Pugnere, K. Qi, X. Qian, J. L. Raaf, R. Raboanary, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, H. T. Rakotondramanana, L. Rakotondravohitra, Y. A. Ramachers, R. Rameika, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Ravat, H. Razafinime, J. S. Real, B. Rebel, D. Redondo, M. Reggiani-Guzzo, T. Rehak, J. Reichenbacher, S. D. Reitzner, A. Renshaw, S. Rescia, F. Resnati, A. Reynolds, G. Riccobene, L. C. J. Rice, K. Rielage, Y. Rigaut, D. Rivera, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, J. Rodriguez Rondon, A. J. Roeth, H. Rogers, S. Rosauro-Alcaraz, M. Rossella, J. Rout, S. Roy, A. Rubbia, C. Rubbia, B. Russell, J. Russell, D. Ruterbories, R. Saakyan, S. Sacerdoti, T. Safford, N. Sahu, P. Sala, N. Samios, M. C. Sanchez, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schaffer, H. Schellman, P. Schlabach, D. Schmitz, K. Scholberg, A. Schukraft, E. Segreto, J. Sensenig, I. Seong, A. Sergi, F. Sergiampietri, D. Sgalaberna, M. H. Shaevitz, S. Shafaq, M. Shamma, H. R. Sharma, R. Sharma, T. Shaw, C. Shepherd-Themistocleous, S. Shin, D. Shooltz, R. Shrock, L. Simard, N. Simos, J. Sinclair, G. Sinev, J. Singh, V. Singh, R. Sipos, F. W. Sippach, G. Sirri, A. Sitraka, K. Siyeon, D. Smargianaki, A. Smith, E. Smith, P. Smith, J. Smolik, M. Smy, P. Snopok, M. Soares Nunes, H. Sobel, M. Soderberg, C. J. Solano Salinas, S. Söldner-Rembold, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, J. Soto-Oton, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, R. Staley, M. Stancari, L. Stanco, H. M. Steiner, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, S. Striganov, A. Stuart, D. Summers, A. Surdo, V. Susic, L. Suter, C. M. Sutera, R. Svoboda, B. Szczerbinska, A. M. Szelc, R. Talaga, H. A. Tanaka, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tatar, R. Tayloe, A. M. Teklu, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, A. Thea, J. L. Thompson, C. Thorn, S. C. Timm, A. Tonazzo, M. Torti, M. Tórtola, F. Tortorici, D. Totani, M. Toups, C. Touramanis, J. Trevor, W. H. Trzaska, Y. T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, M. A. Uchida, J. Urheim, T. Usher, M. R. Vagins, P. Vahle, G. A. Valdiviesso, E. Valencia, Z. Vallari, J. W. F. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, F. Varanini, D. Vargas, G. Varner, J. Vasel, G. Vasseur, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, H. Wang, J. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, M. R. While, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, J. Wolcott, T. Wongjirad, K. Wood, L. Wood, E. Worcester, M. Worcester, C. Wret, W. Wu, Y. Xiao, G. Yang, T. Yang, N. Yershov, K. Yonehara, T. Young, B. Yu, J. Yu, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, M. Zito, S. Zucchelli, J. Zuklin, V. Zutshi, and R. Zwaska
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The deep underground neutrino experiment (DUNE), a 40-kton underground liquid argon time projection chamber experiment, will be sensitive to the electron-neutrino flavor component of the burst of neutrinos expected from the next Galactic core-collapse supernova. Such an observation will bring unique insight into the astrophysics of core collapse as well as into the properties of neutrinos. The general capabilities of DUNE for neutrino detection in the relevant few- to few-tens-of-MeV neutrino energy range will be described. As an example, DUNE’s ability to constrain the $$\nu _e$$ ν e spectral parameters of the neutrino burst will be considered.
Published: 2021
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26. Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment

Author: B. Abi, R. Acciarri, M. A. Acero, G. Adamov, D. Adams, M. Adinolfi, Z. Ahmad, J. Ahmed, T. Alion, S. Alonso Monsalve, C. Alt, J. Anderson, C. Andreopoulos, M. P. Andrews, F. Andrianala, S. Andringa, A. Ankowski, M. Antonova, S. Antusch, A. Aranda-Fernandez, A. Ariga, L. O. Arnold, M. A. Arroyave, J. Asaadi, A. Aurisano, V. Aushev, D. Autiero, F. Azfar, H. Back, J. J. Back, C. Backhouse, P. Baesso, L. Bagby, R. Bajou, S. Balasubramanian, P. Baldi, B. Bambah, F. Barao, G. Barenboim, G. J. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, N. Barros, J. L. Barrow, A. Bashyal, V. Basque, F. Bay, J. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, D. Belver, N. Benekos, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, H. Berns, S. Bertolucci, M. Betancourt, Y. Bezawada, M. Bhattacharjee, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, B. Blanco Siffert, F. D. M. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, M. Bonesini, M. Bongrand, F. Bonini, A. Booth, C. Booth, S. Bordoni, A. Borkum, T. Boschi, N. Bostan, P. Bour, S. B. Boyd, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Brandt, J. Bremer, C. Brew, E. Brianne, S. J. Brice, C. Brizzolari, C. Bromberg, G. Brooijmans, J. Brooke, A. Bross, G. Brunetti, N. Buchanan, H. Budd, D. Caiulo, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, L. Camilleri, A. Caminata, M. Campanelli, D. Caratelli, G. Carini, B. Carlus, P. Carniti, I. Caro Terrazas, H. Carranza, A. Castillo, C. Castromonte, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, C. Chang, E. Chardonnet, A. Chatterjee, S. Chattopadhyay, J. Chaves, H. Chen, M. Chen, Y. Chen, D. Cherdack, C. Chi, S. Childress, A. Chiriacescu, K. Cho, S. Choubey, A. Christensen, D. Christian, G. Christodoulou, E. Church, P. Clarke, T. E. Coan, A. G. Cocco, J. A. B. Coelho, E. Conley, J. M. Conrad, M. Convery, L. Corwin, P. Cotte, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, E. Cristaldo, R. Cross, C. Cuesta, Y. Cui, D. Cussans, M. Dabrowski, H. da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, R. M. De Almeida, P. Debbins, I. De Bonis, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, P. De Lurgio, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. Deptuch, A. De Roeck, V. De Romeri, J. J. De Vries, R. Dharmapalan, M. Dias, F. Diaz, J. S. Díaz, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, N. Dokania, M. J. Dolinski, L. Domine, D. Douglas, F. Drielsma, D. Duchesneau, K. Duffy, P. Dunne, T. Durkin, H. Duyang, O. Dvornikov, D. A. Dwyer, A. S. Dyshkant, M. Eads, D. Edmunds, J. Eisch, S. Emery, A. Ereditato, C. O. Escobar, L. Escudero Sanchez, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, C. Farnese, Y. Farzan, J. Felix, E. Fernandez-Martinez, P. Fernandez Menendez, F. Ferraro, L. Fields, A. Filkins, F. Filthaut, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, S. Fuess, I. Furic, A. P. Furmanski, A. Gago, H. Gallagher, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, R. Gandhi, R. Gandrajula, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, G. Ge, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, D. Gibin, I. Gil-Botella, C. Girerd, A. K. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. V. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, J. A. Gonzalez-Cuevas, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, M. Graham, E. Gramellini, R. Gran, E. Granados, A. Grant, C. Grant, D. Gratieri, P. Green, S. Green, L. Greenler, M. Greenwood, J. Greer, W. C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, V. Guarino, R. Guenette, A. Guglielmi, B. Guo, K. K. Guthikonda, R. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, A. Hackenburg, H. Hadavand, R. Haenni, A. Hahn, J. Haigh, J. Haiston, T. Hamernik, P. Hamilton, J. Han, K. Harder, D. A. Harris, J. Hartnell, T. Hasegawa, R. Hatcher, E. Hazen, A. Heavey, K. M. Heeger, J. Heise, K. Hennessy, S. Henry, M. A. Hernandez Morquecho, K. Herner, L. Hertel, A. S. Hesam, J. Hewes, A. Higuera, T. Hill, S. J. Hillier, A. Himmel, J. Hoff, C. Hohl, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, J. Huang, J. Hugon, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, A. Ioannisian, R. Itay, A. Izmaylov, E. James, B. Jargowsky, F. Jediny, C. Jesùs-Valls, X. Ji, L. Jiang, S. Jiménez, A. Jipa, A. Joglekar, C. Johnson, R. Johnson, B. Jones, S. Jones, C. K. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, F. Kamiya, G. Karagiorgi, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, K. Koehler, L. W. Koerner, S. Kohn, P. P. Koller, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, F. Krennrich, I. Kreslo, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, R. Kumar, C. Kuruppu, V. Kus, T. Kutter, A. Lambert, K. Lande, C. E. Lane, K. Lang, T. Langford, P. Lasorak, D. Last, C. Lastoria, A. Laundrie, A. Lawrence, I. Lazanu, R. LaZur, T. Le, J. Learned, P. LeBrun, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, M. Leyton, L. Li, S. Li, S. W. Li, T. Li, Y. Li, H. Liao, C. S. Lin, S. Lin, A. Lister, B. R. Littlejohn, J. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, K. Loo, D. Lorca, T. Lord, J. M. LoSecco, W. C. Louis, K. B. Luk, X. Luo, N. Lurkin, T. Lux, V. P. Luzio, D. MacFarland, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, A. Maddalena, P. Madigan, S. Magill, K. Mahn, A. Maio, J. A. Maloney, G. Mandrioli, J. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, F. Marinho, A. D. Marino, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martin-Albo, N. Martinez, D. A. Martinez Caicedo, S. Martynenko, K. Mason, A. Mastbaum, M. Masud, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, R. Mazza, A. Mazzacane, E. Mazzucato, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, M. Mellinato, O. Mena, S. Menary, H. Mendez, A. Menegolli, G. Meng, M. D. Messier, W. Metcalf, M. Mewes, H. Meyer, T. Miao, G. Michna, T. Miedema, J. Migenda, R. Milincic, W. Miller, J. Mills, C. Milne, O. Mineev, O. G. Miranda, S. Miryala, C. S. Mishra, S. R. Mishra, A. Mislivec, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, A. Montanari, C. Montanari, D. Montanari, L. M. Montano Zetina, J. Moon, M. Mooney, A. Moor, D. Moreno, B. Morgan, C. Morris, C. Mossey, E. Motuk, C. A. Moura, J. Mousseau, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, D. Navas-Nicolás, N. Nayak, M. Nebot-Guinot, L. Necib, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, D. Newhart, R. Nichol, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, A. Olivares Del Campo, A. Olivier, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, S. Pakvasa, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, J. C. Park, S. Parke, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. J. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. M. Peeters, Y. Penichot, E. Pennacchio, A. Penzo, O. L. G. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, F. Piastra, L. Pickering, F. Pietropaolo, J. Pillow, J. Pinzino, R. Plunkett, R. Poling, X. Pons, N. Poonthottathil, S. Pordes, M. Potekhin, R. Potenza, B. V. K. S. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, S. Prince, G. Prior, D. Pugnere, K. Qi, X. Qian, J. L. Raaf, R. Raboanary, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, H. T. Rakotondramanana, L. Rakotondravohitra, Y. A. Ramachers, R. Rameika, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Ravat, H. Razafinime, J. S. Real, B. Rebel, D. Redondo, M. Reggiani-Guzzo, T. Rehak, J. Reichenbacher, S. D. Reitzner, A. Renshaw, S. Rescia, F. Resnati, A. Reynolds, G. Riccobene, L. C. J. Rice, K. Rielage, Y. Rigaut, D. Rivera, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, J. Rodriguez Rondon, A. J. Roeth, H. Rogers, S. Rosauro-Alcaraz, M. Rossella, J. Rout, S. Roy, A. Rubbia, C. Rubbia, B. Russell, J. Russell, D. Ruterbories, R. Saakyan, S. Sacerdoti, T. Safford, N. Sahu, P. Sala, N. Samios, M. C. Sanchez, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schaffer, H. Schellman, P. Schlabach, D. Schmitz, K. Scholberg, A. Schukraft, E. Segreto, J. Sensenig, I. Seong, A. Sergi, F. Sergiampietri, D. Sgalaberna, M. H. Shaevitz, S. Shafaq, M. Shamma, H. R. Sharma, R. Sharma, T. Shaw, C. Shepherd-Themistocleous, S. Shin, D. Shooltz, R. Shrock, L. Simard, N. Simos, J. Sinclair, G. Sinev, J. Singh, V. Singh, R. Sipos, F. W. Sippach, G. Sirri, A. Sitraka, K. Siyeon, D. Smargianaki, A. Smith, E. Smith, P. Smith, J. Smolik, M. Smy, P. Snopok, M. Soares Nunes, H. Sobel, M. Soderberg, C. J. Solano Salinas, S. Söldner-Rembold, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, J. Soto-Oton, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, R. Staley, M. Stancari, L. Stanco, H. M. Steiner, J. Stewart, B. Stillwell, J. Stock, F. Stocker, D. Stocks, T. Stokes, M. Strait, T. Strauss, S. Striganov, A. Stuart, D. Summers, A. Surdo, V. Susic, L. Suter, C. M. Sutera, R. Svoboda, B. Szczerbinska, A. M. Szelc, R. Talaga, H. A. Tanaka, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tatar, R. Tayloe, A. M. Teklu, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, A. Thea, J. L. Thompson, C. Thorn, S. C. Timm, J. Todd, A. Tonazzo, M. Torti, M. Tortola, F. Tortorici, D. Totani, M. Toups, C. Touramanis, J. Trevor, W. H. Trzaska, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, M. A. Uchida, J. Urheim, T. Usher, M. R. Vagins, P. Vahle, G. A. Valdiviesso, E. Valencia, Z. Vallari, J. W. F. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, F. Varanini, D. Vargas, G. Varner, J. Vasel, G. Vasseur, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, H. Wang, J. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, M. R. While, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, J. Wolcott, T. Wongjirad, K. Wood, L. Wood, E. Worcester, M. Worcester, C. Wret, W. Wu, Y. Xiao, G. Yang, T. Yang, N. Yershov, K. Yonehara, T. Young, B. Yu, J. Yu, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, M. Zhao, Y. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, M. Zito, S. Zucchelli, J. Zuklin, V. Zutshi, and R. Zwaska
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a combination of capable precision detectors, and by the massive far detector system located deep underground. This configuration sets up DUNE as a machine for discovery, as it enables opportunities not only to perform precision neutrino measurements that may uncover deviations from the present three-flavor mixing paradigm, but also to discover new particles and unveil new interactions and symmetries beyond those predicted in the Standard Model (SM). Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE’s sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, neutrino trident production, dark matter from both beam induced and cosmogenic sources, baryon number violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach.
Published: 2021
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27. Learning Scheduling Models from Event Data.

Author: Arik Senderovich, Kyle E. C. Booth, and J. Christopher Beck
Published: 2019

28. A Constraint Programming Approach to Electric Vehicle Routing with Time Windows.

Author: Kyle E. C. Booth and J. Christopher Beck
Published: 2019
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29. Selective optogenetic stimulation of efferent fibers in the vagus nerve of a large mammal

Author: Lindsea C. Booth, Song T. Yao, Alla Korsak, David G.S. Farmer, Sally G. Hood, Daniel McCormick, Quinn Boesley, Angela A. Connelly, Stuart J. McDougall, Willian S. Korim, Sarah-Jane Guild, Svetlana Mastitskaya, Phuong Le, Anja G. Teschemacher, Sergey Kasparov, Gareth L. Ackland, Simon C. Malpas, Robin M. McAllen, Andrew M. Allen, Clive N. May, and Alexander V. Gourine
Subjects: Autonomic nervous system, Brainstem, Neuromodulation, Optogenetic, Vagal preganglionic neurons, Vagus nerve stimulation, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Background: Electrical stimulation applied to individual organs, peripheral nerves, or specific brain regions has been used to treat a range of medical conditions. In cardiovascular disease, autonomic dysfunction contributes to the disease progression and electrical stimulation of the vagus nerve has been pursued as a treatment for the purpose of restoring the autonomic balance. However, this approach lacks selectivity in activating function- and organ-specific vagal fibers and, despite promising results of many preclinical studies, has so far failed to translate into a clinical treatment of cardiovascular disease. Objective: Here we report a successful application of optogenetics for selective stimulation of vagal efferent activity in a large animal model (sheep). Methods and results: Twelve weeks after viral transduction of a subset of vagal motoneurons, strong axonal membrane expression of the excitatory light-sensitive ion channel ChIEF was achieved in the efferent projections innervating thoracic organs and reaching beyond the level of the diaphragm. Blue laser or LED light (>10 mW mm−2; 1 ms pulses) applied to the cervical vagus triggered precisely timed, strong bursts of efferent activity with evoked action potentials propagating at speeds of ∼6 m s−1. Conclusions: These findings demonstrate that in species with a large, multi-fascicled vagus nerve, it is possible to stimulate a specific sub-population of efferent fibers using light at a site remote from the vector delivery, marking an important step towards eventual clinical use of optogenetic technology for autonomic neuromodulation.
Published: 2021
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30. Adjusting neutrino interaction models and evaluating uncertainties using NOvA near detector data

Author: M. A. Acero, P. Adamson, G. Agam, L. Aliaga, T. Alion, V. Allakhverdian, N. Anfimov, A. Antoshkin, L. Asquith, A. Aurisano, A. Back, C. Backhouse, M. Baird, N. Balashov, P. Baldi, B. A. Bambah, S. Bashar, K. Bays, S. Bending, R. Bernstein, V. Bhatnagar, B. Bhuyan, J. Bian, J. Blair, A. C. Booth, P. Bour, R. Bowles, C. Bromberg, N. Buchanan, A. Butkevich, S. Calvez, T. J. Carroll, E. Catano-Mur, S. Childress, B. C. Choudhary, T. E. Coan, M. Colo, L. Corwin, L. Cremonesi, G. S. Davies, P. F. Derwent, P. Ding, Z. Djurcic, D. Doyle, E. C. Dukes, P. Dung, H. Duyang, S. Edayath, R. Ehrlich, M. Elkins, G. J. Feldman, P. Filip, W. Flanagan, J. Franc, M. J. Frank, H. R. Gallagher, R. Gandrajula, F. Gao, S. Germani, A. Giri, R. A. Gomes, M. C. Goodman, V. Grichine, M. Groh, R. Group, B. Guo, A. Habig, F. Hakl, J. Hartnell, R. Hatcher, A. Hatzikoutelis, K. Heller, J. Hewes, A. Himmel, A. Holin, B. Howard, J. Huang, J. Hylen, F. Jediny, C. Johnson, M. Judah, I. Kakorin, D. Kalra, D. M. Kaplan, R. Keloth, O. Klimov, L. W. Koerner, L. Kolupaeva, S. Kotelnikov, Ch. Kullenberg, A. Kumar, C. D. Kuruppu, V. Kus, T. Lackey, K. Lang, L. Li, S. Lin, M. Lokajicek, S. Luchuk, K. Maan, S. Magill, W. A. Mann, M. L. Marshak, M. Martinez-Casales, V. Matveev, B. Mayes, D. P. Méndez, M. D. Messier, H. Meyer, T. Miao, W. H. Miller, S. R. Mishra, A. Mislivec, R. Mohanta, A. Moren, A. Morozova, L. Mualem, M. Muether, S. Mufson, K. Mulder, R. Murphy, J. Musser, D. Naples, N. Nayak, J. K. Nelson, R. Nichol, G. Nikseresht, E. Niner, A. Norman, A. Norrick, T. Nosek, A. Olshevskiy, T. Olson, J. Paley, R. B. Patterson, G. Pawloski, O. Petrova, R. Petti, R. K. Plunkett, A. Rafique, F. Psihas, A. Radovic, V. Raj, B. Ramson, B. Rebel, P. Rojas, V. Ryabov, O. Samoylov, M. C. Sanchez, S. Sánchez Falero, I. S. Seong, P. Shanahan, A. Sheshukov, P. Singh, V. Singh, E. Smith, J. Smolik, P. Snopok, N. Solomey, A. Sousa, K. Soustruznik, M. Strait, L. Suter, A. Sutton, C. Sweeney, R. L. Talaga, B. Tapia Oregui, P. Tas, R. B. Thayyullathil, J. Thomas, E. Tiras, D. Torbunov, J. Tripathi, Y. Torun, J. Urheim, P. Vahle, Z. Vallari, J. Vasel, P. Vokac, T. Vrba, M. Wallbank, T. K. Warburton, M. Wetstein, D. Whittington, S. G. Wojcicki, J. Wolcott, A. Yallappa Dombara, K. Yonehara, S. Yu, Y. Yu, S. Zadorozhnyy, J. Zalesak, Y. Zhang, and R. Zwaska
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The two-detector design of the NOvA neutrino oscillation experiment, in which two functionally identical detectors are exposed to an intense neutrino beam, aids in canceling leading order effects of cross-section uncertainties. However, limited knowledge of neutrino interaction cross sections still gives rise to some of the largest systematic uncertainties in current oscillation measurements. We show contemporary models of neutrino interactions to be discrepant with data from NOvA, consistent with discrepancies seen in other experiments. Adjustments to neutrino interaction models in GENIE are presented, creating an effective model that improves agreement with our data. We also describe systematic uncertainties on these models, including uncertainties on multi-nucleon interactions from a newly developed procedure using NOvA near detector data.
Published: 2020
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31. Accurate brain‐age models for routine clinical MRI examinations

Author: David A. Wood, Sina Kafiabadi, Ayisha Al Busaidi, Emily Guilhem, Antanas Montvila, Jeremy Lynch, Matthew Townend, Siddharth Agarwal, Asif Mazumder, Gareth J. Barker, Sebastien Ourselin, James H. Cole, and Thomas C. Booth
Subjects: Brain age, Deep learning, Convolutional neural networks, Brain-PAD, T2-weighted, Diffusion-weighted, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Convolutional neural networks (CNN) can accurately predict chronological age in healthy individuals from structural MRI brain scans. Potentially, these models could be applied during routine clinical examinations to detect deviations from healthy ageing, including early-stage neurodegeneration. This could have important implications for patient care, drug development, and optimising MRI data collection. However, existing brain-age models are typically optimised for scans which are not part of routine examinations (e.g., volumetric T1-weighted scans), generalise poorly (e.g., to data from different scanner vendors and hospitals etc.), or rely on computationally expensive pre-processing steps which limit real-time clinical utility.Here, we sought to develop a brain-age framework suitable for use during routine clinical head MRI examinations. Using a deep learning-based neuroradiology report classifier, we generated a dataset of 23,302 ‘radiologically normal for age’ head MRI examinations from two large UK hospitals for model training and testing (age range = 18–95 years), and demonstrate fast (< 5 s), accurate (mean absolute error [MAE] < 4 years) age prediction from clinical-grade, minimally processed axial T2-weighted and axial diffusion-weighted scans, with generalisability between hospitals and scanner vendors (Δ MAE < 1 year). The clinical relevance of these brain-age predictions was tested using 228 patients whose MRIs were reported independently by neuroradiologists as showing atrophy ‘excessive for age’. These patients had systematically higher brain-predicted age than chronological age (mean predicted age difference = +5.89 years, 'radiologically normal for age' mean predicted age difference = +0.05 years, p < 0.0001).Our brain-age framework demonstrates feasibility for use as a screening tool during routine hospital examinations to automatically detect older-appearing brains in real-time, with relevance for clinical decision-making and optimising patient pathways.
Published: 2022
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32. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Author: Otto M. Henriksen, María del Mar Álvarez-Torres, Patricia Figueiredo, Gilbert Hangel, Vera C. Keil, Ruben E. Nechifor, Frank Riemer, Kathleen M. Schmainda, Esther A. H. Warnert, Evita C. Wiegers, and Thomas C. Booth
Subjects: magnetic resonance imaging, glioma, perfusion, diffusion, pseudoprogression, monitoring biomarkers, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: ObjectiveSummarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.MethodsExperts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).ResultsHigh-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.ConclusionConsiderable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
Published: 2022
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33. Long-baseline neutrino oscillation physics potential of the DUNE experiment

Author: B. Abi, R. Acciarri, M. A. Acero, G. Adamov, D. Adams, M. Adinolfi, Z. Ahmad, J. Ahmed, T. Alion, S. Alonso Monsalve, C. Alt, J. Anderson, C. Andreopoulos, M. P. Andrews, F. Andrianala, S. Andringa, A. Ankowski, M. Antonova, S. Antusch, A. Aranda-Fernandez, A. Ariga, L. O. Arnold, M. A. Arroyave, J. Asaadi, A. Aurisano, V. Aushev, D. Autiero, F. Azfar, H. Back, J. J. Back, C. Backhouse, P. Baesso, L. Bagby, R. Bajou, S. Balasubramanian, P. Baldi, B. Bambah, F. Barao, G. Barenboim, G. J. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, N. Barros, J. L. Barrow, A. Bashyal, V. Basque, F. Bay, J. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, D. Belver, N. Benekos, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, H. Berns, S. Bertolucci, M. Betancourt, Y. Bezawada, M. Bhattacharjee, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, B. Blanco Siffert, F. D. M. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, M. Bonesini, M. Bongrand, F. Bonini, A. Booth, C. Booth, S. Bordoni, A. Borkum, T. Boschi, N. Bostan, P. Bour, S. B. Boyd, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Brandt, J. Bremer, C. Brew, E. Brianne, S. J. Brice, C. Brizzolari, C. Bromberg, G. Brooijmans, J. Brooke, A. Bross, G. Brunetti, N. Buchanan, H. Budd, D. Caiulo, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, L. Camilleri, A. Caminata, M. Campanelli, D. Caratelli, G. Carini, B. Carlus, P. Carniti, I. Caro Terrazas, H. Carranza, A. Castillo, C. Castromonte, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, C. Chang, E. Chardonnet, A. Chatterjee, S. Chattopadhyay, J. Chaves, H. Chen, M. Chen, Y. Chen, D. Cherdack, C. Chi, S. Childress, A. Chiriacescu, K. Cho, S. Choubey, A. Christensen, D. Christian, G. Christodoulou, E. Church, P. Clarke, T. E. Coan, A. G. Cocco, J. A. B. Coelho, E. Conley, J. M. Conrad, M. Convery, L. Corwin, P. Cotte, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, E. Cristaldo, R. Cross, C. Cuesta, Y. Cui, D. Cussans, M. Dabrowski, H. da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, R. M. De Almeida, P. Debbins, I. De Bonis, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, P. De Lurgio, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. Deptuch, A. De Roeck, V. De Romeri, J. J. De Vries, R. Dharmapalan, M. Dias, F. Diaz, J. S. Díaz, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, N. Dokania, M. J. Dolinski, L. Domine, D. Douglas, F. Drielsma, D. Duchesneau, K. Duffy, P. Dunne, T. Durkin, H. Duyang, O. Dvornikov, D. A. Dwyer, A. S. Dyshkant, M. Eads, D. Edmunds, J. Eisch, S. Emery, A. Ereditato, C. O. Escobar, L. Escudero Sanchez, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, C. Farnese, Y. Farzan, J. Felix, E. Fernandez-Martinez, P. Fernandez Menendez, F. Ferraro, L. Fields, A. Filkins, F. Filthaut, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, S. Fuess, I. Furic, A. P. Furmanski, A. Gago, H. Gallagher, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, R. Gandhi, R. Gandrajula, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, G. Ge, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, D. Gibin, I. Gil-Botella, C. Girerd, A. K. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. V. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, J. A. Gonzalez-Cuevas, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, M. Graham, E. Gramellini, R. Gran, E. Granados, A. Grant, C. Grant, D. Gratieri, P. Green, S. Green, L. Greenler, M. Greenwood, J. Greer, W. C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, V. Guarino, R. Guenette, A. Guglielmi, B. Guo, K. K. Guthikonda, R. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, A. Hackenburg, H. Hadavand, R. Haenni, A. Hahn, J. Haigh, J. Haiston, T. Hamernik, P. Hamilton, J. Han, K. Harder, D. A. Harris, J. Hartnell, T. Hasegawa, R. Hatcher, E. Hazen, A. Heavey, K. M. Heeger, J. Heise, K. Hennessy, S. Henry, M. A. Hernandez Morquecho, K. Herner, L. Hertel, A. S. Hesam, J. Hewes, A. Higuera, T. Hill, S. J. Hillier, A. Himmel, J. Hoff, C. Hohl, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, J. Huang, J. Hugon, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, A. Ioannisian, R. Itay, A. Izmaylov, E. James, B. Jargowsky, F. Jediny, C. Jesùs-Valls, X. Ji, L. Jiang, S. Jiménez, A. Jipa, A. Joglekar, C. Johnson, R. Johnson, B. Jones, S. Jones, C. K. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, F. Kamiya, G. Karagiorgi, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, K. Koehler, L. W. Koerner, S. Kohn, P. P. Koller, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, F. Krennrich, I. Kreslo, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, R. Kumar, C. Kuruppu, V. Kus, T. Kutter, A. Lambert, K. Lande, C. E. Lane, K. Lang, T. Langford, P. Lasorak, D. Last, C. Lastoria, A. Laundrie, A. Lawrence, I. Lazanu, R. LaZur, T. Le, J. Learned, P. LeBrun, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, M. Leyton, L. Li, S. Li, S. W. Li, T. Li, Y. Li, H. Liao, C. S. Lin, S. Lin, A. Lister, B. R. Littlejohn, J. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, K. Loo, D. Lorca, T. Lord, J. M. LoSecco, W. C. Louis, K. B. Luk, X. Luo, N. Lurkin, T. Lux, V. P. Luzio, D. MacFarland, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, A. Maddalena, P. Madigan, S. Magill, K. Mahn, A. Maio, J. A. Maloney, G. Mandrioli, J. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, F. Marinho, A. D. Marino, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martin-Albo, N. Martinez, D. A. Martinez Caicedo, S. Martynenko, K. Mason, A. Mastbaum, M. Masud, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, R. Mazza, A. Mazzacane, E. Mazzucato, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, M. Mellinato, O. Mena, S. Menary, H. Mendez, A. Menegolli, G. Meng, M. D. Messier, W. Metcalf, M. Mewes, H. Meyer, T. Miao, G. Michna, T. Miedema, J. Migenda, R. Milincic, W. Miller, J. Mills, C. Milne, O. Mineev, O. G. Miranda, S. Miryala, C. S. Mishra, S. R. Mishra, A. Mislivec, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, A. Montanari, C. Montanari, D. Montanari, L. M. Montano Zetina, J. Moon, M. Mooney, A. Moor, D. Moreno, B. Morgan, C. Morris, C. Mossey, E. Motuk, C. A. Moura, J. Mousseau, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, D. Navas-Nicolás, N. Nayak, M. Nebot-Guinot, L. Necib, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, D. Newhart, R. Nichol, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, A. Olivares Del Campo, A. Olivier, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, S. Pakvasa, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. J. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. M. Peeters, Y. Penichot, E. Pennacchio, A. Penzo, O. L. G. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, F. Piastra, L. Pickering, F. Pietropaolo, J. Pillow, J. Pinzino, R. Plunkett, R. Poling, X. Pons, N. Poonthottathil, S. Pordes, M. Potekhin, R. Potenza, B. V. K. S. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, S. Prince, G. Prior, D. Pugnere, K. Qi, X. Qian, J. L. Raaf, R. Raboanary, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, H. T. Rakotondramanana, L. Rakotondravohitra, Y. A. Ramachers, R. Rameika, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Ravat, H. Razafinime, J. S. Real, B. Rebel, D. Redondo, M. Reggiani-Guzzo, T. Rehak, J. Reichenbacher, S. D. Reitzner, A. Renshaw, S. Rescia, F. Resnati, A. Reynolds, G. Riccobene, L. C. J. Rice, K. Rielage, Y. Rigaut, D. Rivera, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, J. Rodriguez Rondon, A. J. Roeth, H. Rogers, S. Rosauro-Alcaraz, M. Rossella, J. Rout, S. Roy, A. Rubbia, C. Rubbia, B. Russell, J. Russell, D. Ruterbories, R. Saakyan, S. Sacerdoti, T. Safford, N. Sahu, P. Sala, N. Samios, M. C. Sanchez, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schaffer, H. Schellman, P. Schlabach, D. Schmitz, K. Scholberg, A. Schukraft, E. Segreto, J. Sensenig, I. Seong, A. Sergi, F. Sergiampietri, D. Sgalaberna, M. H. Shaevitz, S. Shafaq, M. Shamma, H. R. Sharma, R. Sharma, T. Shaw, C. Shepherd-Themistocleous, S. Shin, D. Shooltz, R. Shrock, L. Simard, N. Simos, J. Sinclair, G. Sinev, J. Singh, V. Singh, R. Sipos, F. W. Sippach, G. Sirri, A. Sitraka, K. Siyeon, D. Smargianaki, A. Smith, E. Smith, P. Smith, J. Smolik, M. Smy, P. Snopok, M. Soares Nunes, H. Sobel, M. Soderberg, C. J. Solano Salinas, S. Söldner-Rembold, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, J. Soto-Oton, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, R. Staley, M. Stancari, L. Stanco, H. M. Steiner, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, S. Striganov, A. Stuart, D. Summers, A. Surdo, V. Susic, L. Suter, C. M. Sutera, R. Svoboda, B. Szczerbinska, A. M. Szelc, R. Talaga, H. A. Tanaka, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tatar, R. Tayloe, A. M. Teklu, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, A. Thea, J. L. Thompson, C. Thorn, S. C. Timm, A. Tonazzo, M. Torti, M. Tortola, F. Tortorici, D. Totani, M. Toups, C. Touramanis, J. Trevor, W. H. Trzaska, Y. T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, M. A. Uchida, J. Urheim, T. Usher, M. R. Vagins, P. Vahle, G. A. Valdiviesso, E. Valencia, Z. Vallari, J. W. F. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, F. Varanini, D. Vargas, G. Varner, J. Vasel, G. Vasseur, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, H. Wang, J. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, M. R. While, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, J. Wolcott, T. Wongjirad, K. Wood, L. Wood, E. Worcester, M. Worcester, C. Wret, W. Wu, Y. Xiao, G. Yang, T. Yang, N. Yershov, K. Yonehara, T. Young, B. Yu, J. Yu, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, M. Zito, S. Zucchelli, J. Zuklin, V. Zutshi, and R. Zwaska
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass ordering to a precision of 5 $$\sigma $$ σ , for all $$\delta _{\mathrm{CP}}$$ δ CP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3 $$\sigma $$ σ (5 $$\sigma $$ σ ) after an exposure of 5 (10) years, for 50% of all $$\delta _{\mathrm{CP}}$$ δ CP values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to $$\sin ^{2} 2\theta _{13}$$ sin 2 2 θ 13 to current reactor experiments.
Published: 2020
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34. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Author: Thomas C. Booth, Evita C. Wiegers, Esther A. H. Warnert, Kathleen M. Schmainda, Frank Riemer, Ruben E. Nechifor, Vera C. Keil, Gilbert Hangel, Patrícia Figueiredo, Maria Del Mar Álvarez-Torres, and Otto M. Henriksen
Subjects: high-grade glioma, glioblastoma, treatment response, monitoring biomarker, MRI, spectroscopy, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: ObjectiveTo summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.MethodsThe current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).ResultsThe biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.ConclusionAdvanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
Published: 2022
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35. Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies

Author: Thomas C. Booth, Mariusz Grzeda, Alysha Chelliah, Andrei Roman, Ayisha Al Busaidi, Carmen Dragos, Haris Shuaib, Aysha Luis, Ayesha Mirchandani, Burcu Alparslan, Nina Mansoor, Jose Lavrador, Francesco Vergani, Keyoumars Ashkan, Marc Modat, and Sebastien Ourselin
Subjects: glioblastoma, machine learning, monitoring biomarkers, meta-analysis, artificial intelligence, treatment response, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: ObjectiveMonitoring biomarkers using machine learning (ML) may determine glioblastoma treatment response. We systematically reviewed quality and performance accuracy of recently published studies.MethodsFollowing Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Diagnostic Test Accuracy, we extracted articles from MEDLINE, EMBASE and Cochrane Register between 09/2018–01/2021. Included study participants were adults with glioblastoma having undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide), and follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics, the target condition). Using Quality Assessment of Diagnostic Accuracy Studies Two/Checklist for Artificial Intelligence in Medical Imaging, we assessed bias risk and applicability concerns. We determined test set performance accuracy (sensitivity, specificity, precision, F1-score, balanced accuracy). We used a bivariate random-effect model to determine pooled sensitivity, specificity, area-under the receiver operator characteristic curve (ROC-AUC). Pooled measures of balanced accuracy, positive/negative likelihood ratios (PLR/NLR) and diagnostic odds ratio (DOR) were calculated. PROSPERO registered (CRD42021261965).ResultsEighteen studies were included (1335/384 patients for training/testing respectively). Small patient numbers, high bias risk, applicability concerns (particularly confounding in reference standard and patient selection) and low level of evidence, allow limited conclusions from studies. Ten studies (10/18, 56%) included in meta-analysis gave 0.769 (0.649-0.858) sensitivity [pooled (95% CI)]; 0.648 (0.749-0.532) specificity; 0.706 (0.623-0.779) balanced accuracy; 2.220 (1.560-3.140) PLR; 0.366 (0.213-0.572) NLR; 6.670 (2.800-13.500) DOR; 0.765 ROC-AUC.ConclusionML models using MRI features to distinguish between progression and mimics appear to demonstrate good diagnostic performance. However, study quality and design require improvement.
Published: 2022
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36. S233: THERAPEUTIC GENE EDITING OF T CELLS CORRECTS CTLA4 INSUFFICIENCY.

Author: T. Fox, B. Houghton, L. Petersone, N. Edner, O. Preham, E. Waters, C. Hinze, A. McKenna, C. Williams, A. Kennedy, A. Pesenacker, P. Genovese, L. Walker, S. Burns, D. Sansom, C. Booth, and E. Morris
Subjects: Diseases of the blood and blood-forming organs, RC633-647.5
Published: 2022
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37. Comparing and Integrating Constraint Programming and Temporal Planning for Quantum Circuit Compilation.

Author: Kyle E. C. Booth, Minh Do, J. Christopher Beck, Eleanor Gilbert Rieffel, Davide Venturelli, and Jeremy Frank
Published: 2018

38. An Update on Machine Learning in Neuro-Oncology Diagnostics.

Author: Thomas C. Booth
Published: 2018
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39. Label-free detection of conformational changes in switchable DNA nanostructures with microwave microfluidics

Author: Angela C. Stelson, Minghui Liu, Charles A. E. Little, Christian J. Long, Nathan D. Orloff, Nicholas Stephanopoulos, and James C. Booth
Subjects: Science
Abstract: Methods to study conformational changes in biomolecules are limited in resolution and require labelling or other modifications of target analytes. Here the authors present a label-free, microwave microfluidic approach to detect conformational changes of DNA nanostructures based on ionic conductivity.
Published: 2019
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40. Bariatric Surgery and Psychological Health: A Randomised Clinical Trial in Patients with Obesity and Type 2 Diabetes

Author: Lynn M. Murton, Lindsay D. Plank, Rick Cutfield, David Kim, Michael W. C. Booth, Rinki Murphy, and Anna Serlachius
Subjects: Nutrition and Dietetics, Endocrinology, Diabetes and Metabolism, Surgery
Abstract: Purpose This study investigated the impact of either Roux-en-Y gastric bypass with silastic ring (SR-RYGB) or sleeve gastrectomy (SG) types of bariatric surgery on psychological health and explored the role of pre-existing depressive symptoms on weight loss. Materials and Methods A total of 114 participants with obesity and type 2 diabetes were randomized to receive SR-RYGB or SG at a single centre. Data from the Hospital Anxiety and Depression Scale (HADS), RAND 36-item Health Survey and body weight were collected before surgery and annually for 5 years. Results Sixteen patients were lost to follow-up at 5 years. Of the 98 patients who completed 5-year psychological follow-up assessments, 13 had mild to severe depressive symptoms (SR-RYGB n = 6, SG n = 7). SR-RYGB and SG resulted in similar psychological health improvement but percent weight loss at 5 years was greater for SR-RYGB by 10.6% (95% CI: 7.2 to 14.0, P Conclusion Patients receiving either SR-RYGB or SG had comparable psychosocial functioning, which was maintained to 5 years post-surgery. Pre-existing depressive symptoms did not affect weight loss achieved at 5 years. These findings confirm previous longitudinal studies demonstrating that bariatric surgery is generally associated with improved psychosocial functioning. Graphical Abstract
Published: 2023

41. A Position Statement on the Utility of Interval Imaging in Standard of Care Brain Tumour Management: Defining the Evidence Gap and Opportunities for Future Research

Author: Thomas C. Booth, Gerard Thompson, Helen Bulbeck, Florien Boele, Craig Buckley, Jorge Cardoso, Liane Dos Santos Canas, David Jenkinson, Keyoumars Ashkan, Jack Kreindler, Nicky Huskens, Aysha Luis, Catherine McBain, Samantha J. Mills, Marc Modat, Nick Morley, Caroline Murphy, Sebastian Ourselin, Mark Pennington, James Powell, David Summers, Adam D. Waldman, Colin Watts, Matthew Williams, Robin Grant, and Michael D. Jenkinson
Subjects: glioblastoma, high grade glioma, glioma, meningioma, interval imaging, magnetic resonance imaging, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Objectiv eTo summarise current evidence for the utility of interval imaging in monitoring disease in adult brain tumours, and to develop a position for future evidence gathering while incorporating the application of data science and health economics.MethodsExperts in ‘interval imaging’ (imaging at pre-planned time-points to assess tumour status); data science; health economics, trial management of adult brain tumours, and patient representatives convened in London, UK. The current evidence on the use of interval imaging for monitoring brain tumours was reviewed. To improve the evidence that interval imaging has a role in disease management, we discussed specific themes of data science, health economics, statistical considerations, patient and carer perspectives, and multi-centre study design. Suggestions for future studies aimed at filling knowledge gaps were discussed.ResultsMeningioma and glioma were identified as priorities for interval imaging utility analysis. The “monitoring biomarkers” most commonly used in adult brain tumour patients were standard structural MRI features. Interval imaging was commonly scheduled to provide reported imaging prior to planned, regular clinic visits. There is limited evidence relating interval imaging in the absence of clinical deterioration to management change that alters morbidity, mortality, quality of life, or resource use. Progression-free survival is confounded as an outcome measure when using structural MRI in glioma. Uncertainty from imaging causes distress for some patients and their caregivers, while for others it provides an important indicator of disease activity. Any study design that changes imaging regimens should consider the potential for influencing current or planned therapeutic trials, ensure that opportunity costs are measured, and capture indirect benefits and added value.ConclusionEvidence for the value, and therefore utility, of regular interval imaging is currently lacking. Ongoing collaborative efforts will improve trial design and generate the evidence to optimise monitoring imaging biomarkers in standard of care brain tumour management.
Published: 2021
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42. Influence of interspecies interactions on the spatial organization of dual species bacterial communities

Author: Sean C. Booth and Scott A. Rice
Subjects: Pseudomonas, Klebsiella, Biofilm, Colony, Interspecies interactions, Model community, Biotechnology, TP248.13-248.65, Microbiology, QR1-502
Abstract: Interspecies interactions in bacterial biofilms have important impacts on the composition and function of communities in natural and engineered systems. To investigate these interactions, synthetic communities provide experimentally tractable systems. Biofilms grown on agar-surfaces have been used for investigating the eco-evolutionary and biophysical forces that determine community composition and spatial distribution of bacteria. Prior studies have used genetically identical bacterial strains and strains with specific mutations, that express different fluorescent proteins, to investigate intraspecies interactions. Here, we investigated interspecies interactions and, specifically, determined the community composition and spatial distribution in synthetic communities of Pseudomonas aeruginosa, Pseudomonas protegens and Klebsiella pneumoniae. Using quantitative microscopic imaging, we found that interspecies interactions in multispecies colonies were influenced by type IV pilus mediated motility, extracellular matrix secretion, environmental parameters, and these effects were also influenced by the specific partner in the dual species combinations. These results indicate that the patterns observable in mixed species colonies can be used to understand the mechanisms that drive interspecies interactions, which are dependent on the interplay between specific species’ physiology and environmental conditions.
Published: 2020
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43. Reporting on the status, trends, and drivers of algal blooms on Lake of the Woods using satellite-derived bloom indices (2002–2021)

Author: C.E. Binding, C. Zeng, L. Pizzolato, C. Booth, R. Valipour, P. Fong, A. Zastepa, and T. Pascoe
Subjects: Ecology, Aquatic Science, Ecology, Evolution, Behavior and Systematics
Published: 2023

44. Fibroblast Activation Protein–Targeted Radioligand Therapy for Treatment of Solid Tumors

Author: Spencer D. Lindeman, Ramesh Mukkamala, Autumn Horner, Pooja Tudi, Owen C. Booth, Roxanne Huff, Joshua Hinsey, Anders Hovstadius, Peter Martone, Fenghua Zhang, Madduri Srinivasarao, Abigail Cox, and Philip S. Low
Subjects: Radiology, Nuclear Medicine and imaging
Published: 2022

45. Feasibility of reporting results of large randomised controlled trials to participants: experience from the Fluoxetine Or Control Under Supervision (FOCUS) trial

Author: Martin Dennis, D Cohen, A Thompson, Graham Ellis, A Khan, L Hunt, X Huang, J Andrews, J Foot, S Wong, A Stevens, D Bailey, S Johnston, R Robinson, A Johnson, S Williams, T Smith, A Ahmed, S Bloom, L Sekaran, D Singh, F Smith, R Greenwood, R Brown, J White, S Arif, S Ross, S Trippier, S Levy, B Patel, M Khan, A Thomas, S Brown, V Jones, D Wood, U Khan, P Nair, A Smith, G Hann, R Williams, M Cooper, S Jackson, M Hassan, P Kumar, A Metcalf, R Patel, A Wright, S Khan, A Bell, M Robinson, K Jones, S Alam, R Shah, J Simpson, K Ali, K Miller, K Kennedy, S Ahmed, L Thomas, M Scott, S Nelson, S Clayton, L Zhang, B Charles, P Lopez, A Fleming, C Lambert, A Shah, J Wong, David Burgess, L Wilson, A Siddiqui, S Kumar, A Hassan, D Cooke, M Williams, P Cooper, S Graham, S Morrison, M Holland, C Green, C Edwards, K Subramanian, K Patel, J Mitchell, J Stewart, S Keenan, C Duggan, S McKenna, M Ward, S Walker, L Wright, M Edwards, N Sattar, J Mcgee, R Butler, M Wilkinson, C Kelly, R Cowan, C Brown, K Moore, L Denny, S Patel, R Rodriguez, J Allen, M Kalita, Gillian Mead, A Bowring, A Edwards, J Scott, J Drew, L Dixon, K Burton, E Brown, E Epstein, R Miller, F Reid, A Jones, P Murphy, A Ali, N Ahmad, S Noor, C Leonard, A Nair, M Naeem, E Douglas, J Thompson, R Evans, C Jenkins, J Wilson, R Anderson, H Wilson, H Stone, J Ward, L Greenhalgh, P Walker, A Hill, K Stagg, S Naqvi, R Scott, M Hughes, P Jones, M Simpson, K Elliott, M Davy, S Young, Karen Innes, Pippa Tyrrell, A David, Steff Lewis, A Bwalya, C Buckley, S Kelly, C Thomas, I Kane, M Hussain, S Shah, J Roberts, D Morales, C McInnes, N Khan, N Weir, L Hill, K Kavanagh, R Clarke, P Thompson, J Price, J Ball, L Benton, E Walton, E Walker, L Burgess, K McCormick, L Wade, C Anderson, S Stevenson, R Blackburn, L Brown, B Clarke, T Khan, S Dhar, L Harrison, S Bell, D Buchanan, A Deary, J Drever, R Fraser, K Innes, C McGill, D Perry, A Barugh, G Blair, Y Chun, E Maschauer, J Forbes, M Hackett, G Hankey, A House, E Lundström, Peter Sandercock, Judith Williamson, Graeme Hankey, Maree Hackett, Veronica Murray, Ray French, David Stott, M MacLeod, F Sullivan, P Langhorne, H Rodgers, N Hunter, R Parakramawansha, A Fazal, P Taylor, W Rutherford, R Buchan, A MacRaild, R Paulton, S Burgess, D McGowan, J Skwarski, F Proudfoot, J Perry, J Bamford, C Bedford, D Waugh, E Veraque, M Kambafwile, L Makawa, P Smalley, M Randall, L Idrovo, T Thirugnana-Chandran, R Vowden, J Jackson, A Bhalla, C Tam, A Rudd, C Gibbs, J Birns, L Lee Carbon, E Cattermole, A Cape, L hurley, K Marks, S Kullane, N Smyth, E Giallombardo, C Eglinton, D Dellafera, P Reidy, M Pitt, L Sykes, A Frith, V Croome, J Duffy, M Hancevic, L Kerwood, C Narh, C Merritt, J Willson, T Jackson, H Bowler, C Kamara, J Howe, K Stocks, G Dunn, K Endean, F Claydon, S Duty, K Harkness, E Richards, M Meegada, A Maatouk, L Barron, K Dakin, R Lindert, A Majid, P Rana, C Brighouse-Johnson, J Greig, M Kyu, S Prasad, B Mclean, I Alam, Z Ahmed, C Roffe, S Brammer, A Barry, C Beardmore, K Finney, P Hollinshead, J Grocott, I Natarajan, J Chembala, R Sanyal, S Lijko, N Abano, A Remegoso, P Ferdinand, S Stevens, C Stephen, P Whitmore, A Butler, C Causley, R Varquez, G Muddegowda, R Carpio, J Hiden, H Denic, J Sword, F Hall, J Cageao, R Curwen, M James, P Mudd, C Roughan, H Kingwell, A Hemsley, C Lohan, S Davenport, T Chapter, M Hough, D Strain, K Gupwell, A Goff, E Cusack, S Todd, R Partridge, G Jennings, K Thorpe, J Stephenson, K Littlewood, M Barber, F Brodie, S Marshall, D Esson, I Coburn, F Ross, V Withers, E Bowie, H Barcroft, L Miller, P Willcoxson, M Keeling, M Donninson, D Daniel, J Coyle, M Elliott, P Wanklyn, J Wightman, E Iveson, A Porteous, N Dyer, M Haritakis, J Bell, C Emms, P Wood, P Cottrell, L Doughty, L Carr, C Anazodo, M O Neill, J Westmoreland, R Mir, C Donne, E Bamford, P Clark Brown, A Stanners, I Ghouri, A Needle, M Eastwood, M Carpenter, P Datta, R Davey, F Razik, G Bateman, J Archer, V Balasubramanian, L Jackson, R Bowers, J Ellam, K Norton, P Guyler, S Tysoe, P Harman, A Kundu, T Dowling, S Chandler, O Omodunbi, T Loganathan, S Kunhunny, D Sinha, M Sheppard, S Kelavkar, K Ng, A Ropun, L Kamuriwo, R Orath Prabakaran, E France, S Rashmi, D Mangion, C Constantin, S Markova, A Hardwick, J Borley, L De Michele Hock, T Lawrence, K Netherton, R Spencer, H Palmer, M Soliman, S Leach, J Sharma, C Taylor, I Wahishi, A Fields, S Butler, J Hindle, E Watson, C Hewitt, C Cullen, D Hamill, Z Mellor, T Fluskey, V Hankin, A Keeling, R Durairaj, J Peters, D Shackcloth, R Tangney, T Hlaing, V Sutton, J Ewing, C Patterson, H Ramadan, R Bellfield, U Hamid, M Hooley, R Ghulam, L Masters, W Gaba, O Quinn, M Tate, N Mohammed, S Sethuraman, L Alwis, K Bharaj, R Pattni, F Justin, M Chauhan, L Eldridge, S Mintias, J Palmones, C Holmes, L Guthrie, N Devitt, J Leonard, M Osborn, L Ball, A Steele, E Dodd, A Holloway, P Baker, I Penwarden, S Caine, S Clarke, L Dow, R Wynn-Williams, J Kennedy, A DeVeciana, P Mathieson, I Reckless, R Teal, G Ford, P Mccann, G Cluckie, G Howell, J Ayer, B Moynihan, R Ghatala, G Cloud, N Al-Samarrai, F Watson, T Adedoyin, N Chopra, L Choy, N Clarke, A Dainty, A Blight, J Selvarajah, W Smith, F Moreton, A Welch, D Kalladka, B Cheripelli, A Lush, S El Tawil, N Day, K Montgomery, H Hamilton, D Ritchie, S Ramachandra, K McLeish, B Badiani, M Abdul-Saheb, A Chamberlain, M Mpelembue, R Bathula, M Lang, J Devine, L Southworth, N Epie, E Owoyele, F Guo, A Oshodi, V Sudkeo, K Thavanesan, D Tiwari, C Ovington, E Rogers, R Bower, B Longland, O David, A Hogan, S Loganathan, C Cox, S Orr, M Keltos, K Rashed, B Williams-Yesson, J Board, S De Bruijn, C Vickers, S Board, J Allison, E Keeling, T Duckett, D Donaldson, C Barron, L Balian, T England, A Hedstrom, E Bedford, M Harper, E Melikyan, W Abbott, M Goldsworthy, M Srinivasan, I Mukherjee, U Ghani, A Yeomans, F Hurford, R Chapman, S Shahzad, N Motherwell, L Tonks, R Young, D Dutta, P Brown, F Davis, J Turfrey, M Obaid, B Cartwright, B Topia, J Spurway, C Hughes, S OConnell, K Collins, R Bakawala, K Chatterjee, T Webster, S Haider, P Rushworth, F Macleod, C Perkins, A Nallasivan, E Burns, S Leason, T Carter, S Seagrave, E Sami, S Parkinson, L Armstrong, S Mawer, G Darnbrook, C Booth, B Hairsine, S Williamson, F Farquhar, B Esisi, T Cassidy, B McClelland, G Mankin, M Bokhari, D Sproates, S Hurdowar, N Sukhdeep, S Razak, N Upton, A Hashmi, K Osman, K Fotherby, A Willberry, D Morgan, G Sahota, K Jennings-Preece, D Butler, K Kauldhar, F Harrington, A Mate, J Skewes, K Adie, K Bond, G Courtauld, C Schofield, L Lucas, A James, S Ellis, B Maund, L Allsop, C Brodie, E Driver, K Harris, M Drake, E Thomas, M Burn, A Hamilton, S Mahalingam, A Benford, D Hilton, A Misra, L Hazell, K Ofori, M Mathew, S Dayal, I Burn, D Bruce, R Burnip, R Hayman, P Earnshaw, P Gamble, S Dima, M Dhakal, G Rogers, L Stephenson, R Nendick, Y Pai, K Nyo, V Cvoro, M Couser, A Tachtatzis, K Ullah, R Cain, N Chapman, S Pound, S McAuley, D Hargroves, B Ransom, K Mears, K Griffiths, L Cowie, T Hammond, T Webb, I Balogun, H Rudenko, A Thomson, D Ceccarelli, A Gillian, E Beranova, A Verrion, N Chattha, N Schumacher, A Bahk, D Sims, R Tongue, M Willmot, C Sutton, E Littleton, J Khaira, S Maiden, J Cunningham, Y Chin, M Bates, K Ahlquist, J Breeds, T Sargent, L Latter, A Pitt Ford, T Levett, N Gainsborough, A Dunne, E Barbon, S Hervey, S Ragab, T Sandell, C Dickson, S Power, J Dube, N Evans, B Wadams, S Elitova, B Aubrey, T Garcia, J Mcilmoyle, C Dickinson, C Jeffs, J Howard, C Armer, J Frudd, A Potter, S Donaldson, D Collas, S Sundayi, L Denham, D Oza, M Bhandari, S Ispoglou, K Sharobeem, A Hayes, J Howard-Brown, S Shanu, S Billingham, G Howard, E Wood, V Pressly, P Crawford, H Burton, A Walters, J Marigold, R Said, C Allen, S Evans, S Egerton, J Hakkak, R Lampard, S Tsang, R Creeden, I Gartrell, F Price, J Pryor, A Hedges, L Moseley, L Mercer, E Warburton, D Handley, S Finlay, N Hannon, A Espanol, H Markus, D Chandrasena, J Sesay, D Hayden, H Hayhoe, J Macdonald, M Bolton, C Farron, E Amis, D Day, A Culbert, L Whitehead, S Crisp, J OConnell, E Osborne, R Beard, P Corrigan, L Mokoena, M Myint, R Krishnamurthy, A Azim, S Whitworth, A Nicolson, M Krasinska-Chavez, J Imam, S Chaplin, J Curtis, L Wood, C McGhee, A Smart, F Donaldson, J Blackburn, C Copeland, P Fitzsimmons, G Fletcher, A Manoj, P Cox, L Trainor, H Allsop, U Sukys, S Valentine, D Jarrett, K Dodsworth, M Wands, C Watkinson, W Golding, J Tandy, K Yip, C James, Y Davies, A Suttling, K Nagaratnam, N Mannava, N Haque, N Shields, K Preston, G Mason, K Short, G Uitenbosch, G Lumsdale, H Emsley, S Sultan, B Walmsley, D Doyle, A McLoughlin, L Hough, B Gregary, S Raj, A Maney, S Blane, G Gamble, A Hague, B Duran, R Whiting, M Harvey, J Homan, L Foote, L Graham, C Lane, L Kemp, J Rowe, H Durman, L Brotherton, N Hunt, A Whitcher, C Pawley, P Sutton, S Mcdonald, D Pak, A Wiltshire, J Balami, C Self, J Jagger, G Healey, M Crofts, A Chakrabarti, C Hmu, J Keshet-Price, G Ravenhill, C Grimmer, T Soe, I Potter, P Tam, M Langley, M Christie, J Irvine, A Joyson, F Annison, D Christie, C Meneses, V Taylor, J Furnace, H Gow, Y Abousleiman, S Goshawk, J Purcell, T Beadling, S Collins, S Sangaralingham, E Munuswamy Vaiyapuri, M Landicho, Y Begum, S Mutton, J Lowe, I Wiggam, S Tauro, S Cuddy, B Wells, A Mohd Nor, N Persad, M Weinling, S Weatherby, D Lashley, A Pace, A Mucha, J Baker, M Marner, J Westcott, N Wilmshurst, D Chadha, M Fairweather, D Walstow, R Fong, M Krishnan, H Thompson Jones, C Lynda, C Clements, T Anjum, S Sharon, D Lynne, S Tucker, D Colwill, E Vasileiadis, A Parry, C Mason, M Holden, K Petrides, T Nishiyama, H Mehta, S Mumani, C Almadenboyle, S Carson, M Stirling, E Tenbruck, D Broughton, A Annamalai, D Tryambake, A Skotnicka, A Sigsworth, S Whitehouse, J Pagan, A Pusalkar, H Beadle, K Chan, P Dangri, A Asokanathan, A Rana, S Gohil, K Crabtree, A Cook, M Massyn, P Aruldoss, S Dabbagh, T Black, R Fennelly, L Nardone, V DiMartino, A Anthony, D Mead, M Tribbeck, B Affley, C Sunderland, E Young, L Goldenberg, P Wilkinson, L Abbott, R Nari, S Lock, A Shakhon, R Pereira, M DSouza, S Dunn, N Cron, A Mckenna, R Sivakumar, S Cook, J Ngeh, R Saksena, J Ketley-O'Donel, R Needle, E Chinery, L Howaniec, C Watchurst, R Erande, M Brezitski, N Passeron, E Elliott, N Oji, D Austin, A Banaras, C Hogan, T Corbett, M Kidd, G Hull, S Punekar, J Nevinson, H Penney, W Wareing, N Hayes, K Bunworth, L Connell, K Mahawish, G Drummond, N Sengupta, M Metiu, C Gonzalez, J Margalef, S Funnell, G Peters, I Chadbourn, H Proeschel, P Ashcroft, S Sharpe, P Cook, D Jenkinson, D Kelly, H Bray, G Gunathilagan, S Tilbey, S Abubakar, A Rajapakse, A Nasar, J Janbieh, L Otter, I Wynter, S Haigh, R Boulton, J Burgoyne, A Boulton, J Vassallo, A Hasan, L Orrell, S Qamar, D Leonard, E Hewitt, M Haque, J Awolesi, E Bradshaw, A Kent, A Hynes, E Nurse, S Raza, U Pallikona, B Edwards, G Morgan, H Tench, R Loosley, K Dennett, T Trugeon-Smith, D Robson, R Rayessa, A Abdul-Hamid, V Lowthorpe, K Mitchelson, E Clarkson, H Rhian, R Kirthivasan, J Topliffe, R Keskeys, F McNeela, E Bohannan, L Cooper, G Zachariah, F Cairns, T James, L Fergey, S Smolen, A Lyle, E Cannon, S Omer, S Mavinamane, S Meenakshisundaram, L Ranga, J Bate, M Hargreaves, S Dealing, S Amlani, G Gulli, M Hawkes-Blackburn, L Francis, S Holland, A Peacocke, J Amero, M Burova, O Speirs, S Brotheridge, S Al Hussayni, H Lyon, C Hare, J Featherstone, M Goorah, J Walford, D Rusk, D Sutton, F Patel, S Duberley, K Hayes, E Ahmed El Nour, S Dyer, E Temlett, J Paterson, S Honour, C Box, R Furness, E Orugun, H Crowther, R Glover, C Brewer, S Thornthwaite, M Sein, K Haque, L Bailey, E Gibson, L Brookes, K Rotchell, K Waltho, C Lindley, P Harlekar, C Culmsee, L Booth, J Ritchie, N Mackenzie, J Barker, M Haley, D Cotterill, L Lane, D Simmons, R Warinton, G Saunders, H Dymond, S Kidd, C Little, Y Neves-Silva, B Nevajda, M Villaruel, U Umasankar, A Man, N Gadi, N Christmas, R Ladner, R Rangasamy, G Butt, W Alvares, M Power, S Hagan, K Dynan, S Crothers, B Wroath, G Douris, D Vahidassr, B Gallen, C McGoldrick, M Bhattad, J Putteril, R Gallifent, E Makanju, M Lepore, C McRedmond, L Arundell, A Goulding, K Kawafi, P Jacob, L Turner, N Saravanan, L Johnson, D Morse, R Namushi, S Humphrey, M Salehin, S Tinsley, T Jones, L Garcia-Alen, L Kalathil, N Gautam, J Horton, J Meir, E Margerum, A Ritchings, K Amor, V Nadarajan, J Laurence, S Fung Lo, S Melander, P Nicholas, E Woodford, G McKenzie, V Le, J Crause, P OMahony, C Orefo, C McDonald, E Osikominu, G Appiatse, A Wardale, M Augustin, R Luder, M Bhargava, G Bhome, V Johnson, D Chesser, H Bridger, E Murali, A Burns, J Graham, M Duffy, E Pitcher, J Gaylard, J Newman, S Punnoose, S Oakley, V Murray, C Bent, R Walker, K Purohit, A Rees, S Besley, O Chohan, L Argandona, L Cuenoud, H Hassan, E Erumere, A OCallaghan, O Redjep, G Auld, P Gompertz, A Song, R Hungwe, H Kabash, T Tarkas, G Livingstone, F Butler, S Bradfield, L Gordon, J Schmit, A Wijewardane, C Medcalf, T Edmunds, R Wills, and C Peixoto
Subjects: Medicine
Abstract: Objectives Informing research participants of the results of studies in which they took part is viewed as an ethical imperative. However, there is little guidance in the literature about how to do this. The Fluoxetine Or Control Under Supervision trial randomised 3127 patients with a recent acute stroke to 6 months of fluoxetine or placebo and was published in the Lancet on 5 December 2018. The trial team decided to inform the participants of the results at exactly the same time as the Lancet publication, and also whether they had been allocated fluoxetine or placebo. In this report, we describe how we informed participants of the results.Design In the 6-month and 12-month follow-up questionnaires, we invited participants to provide an email address if they wished to be informed of the results of the trial. We re-opened our trial telephone helpline between 5 December 2018 and 31 March 2019.Setting UK stroke services.Participants 3127 participants were randomised. 2847 returned 6-month follow-up forms and 2703 returned 12-month follow-up forms; the remaining participants had died (380), withdrawn consent or did not respond.Results Of those returning follow-up questionnaires, a total of 1845 email addresses were provided and a further 50 people requested results to be sent by post. Results were sent to all email and postal addresses provided; 309 emails were returned unrecognised. Seventeen people replied, of whom three called the helpline and the rest responded by email.Conclusion It is feasible to disseminate results of large trials to research participants, though only around 60% of those randomised wanted to receive the results. The system we developed was efficient and required very little resource, and could be replicated by trialists in the future.Trial registration number ISRCTN83290762; Post-results.
Published: 2020
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46. Risk factors for MEK-associated retinopathy in patients with advanced melanoma treated with combination BRAF and MEK inhibitor therapy

Author: Andrew E. C. Booth, Ashley M. Hopkins, Andrew Rowland, Ganessan Kichenadasse, Justine R. Smith, and Michael J. Sorich
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract: Background: Retinopathy is a common adverse event with mitogen-activated extracellular signal-regulated kinase (MEK) inhibitors. Little is known about the pathophysiology of MEK inhibitor-associated retinopathy (MEKAR). Since MEKAR has many similarities to central serous chorioretinopathy (CSCR), they may share common risk factors. The aim of this study was to evaluate the association between baseline characteristics and MEKAR in melanoma patients initiating MEK inhibitor treatment. Methods: Data from patients treated with cobimetinib and vemurafenib for advanced melanoma in the coBRIM trial were subjected to secondary analysis. Consistent with CSCR risk factors, assessed baseline characteristics included: age, gender, past ocular disease, weight, hypertension, diabetes, dyslipidemia, glomerular filtration rate (eGFR) and corticosteroid use. Associations between characteristics and retinopathy events (any grade and symptomatic) were evaluated using univariate logistic regression and represented as odds ratios (OR). Results: A total of 247 patients were treated with cobimetinib and vemurafenib, of whom 72 (29%) had retinopathy of any grade and 33 (13%) had symptomatic retinopathy. Patients with a history of ocular disease were at significantly higher risk of retinopathy (any grade, 44%; symptomatic, 22%) than those with no ocular disease history (any grade, 22%; symptomatic, 10%). Individuals with a history of ocular inflammation or infection were at highest risk: 4 of 5 developed symptomatic retinopathy during MEK inhibitor therapy. Increased age was associated with a higher risk of any grade retinopathy {decade increase OR [95% confidence interval (CI)] = 1.03 (1.01–1.05); p = 0.009}, while increasing eGFR was significantly associated with a decreased risk of any grade retinopathy [0.98 (0.96–0.99); p = 0.004]; the associations were not statistically significant with symptomatic retinopathy. Other assessed CSCR risk factors were not significantly associated with MEKAR. Conclusion: Age, glomerular filtration rate and history of ocular disease (particularly inflammatory eye disease) were associated with a risk of MEK inhibitor induced retinopathy. Patients who are at increased risk of MEKAR may benefit from more regular ophthalmologic assessment during treatment.
Published: 2020
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47. Logic-Based Decomposition Methods for the Travelling Purchaser Problem.

Author: Kyle E. C. Booth, Tony T. Tran, and J. Christopher Beck
Published: 2016
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48. A Constraint Programming Approach to Multi-Robot Task Allocation and Scheduling in Retirement Homes.

Author: Kyle E. C. Booth, Goldie Nejat, and J. Christopher Beck
Published: 2016
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49. Quantum-accelerated constraint programming

Author: Kyle E. C. Booth, Bryan O'Gorman, Jeffrey Marshall, Stuart Hadfield, and Eleanor Rieffel
Subjects: Physics, QC1-999
Abstract: Constraint programming (CP) is a paradigm used to model and solve constraint satisfaction and combinatorial optimization problems. In CP, problems are modeled with constraints that describe acceptable solutions and solved with backtracking tree search augmented with logical inference. In this paper, we show how quantum algorithms can accelerate CP, at both the levels of inference and search. Leveraging existing quantum algorithms, we introduce a quantum-accelerated filtering algorithm for the $\texttt{alldifferent}$ global constraint and discuss its applicability to a broader family of global constraints with similar structure. We propose frameworks for the integration of quantum filtering algorithms within both classical and quantum backtracking search schemes, including a novel hybrid classical-quantum backtracking search method. This work suggests that CP is a promising candidate application for early fault-tolerant quantum computers and beyond.
Published: 2021
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50. Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, G. Adamov, D. Adams, M. Adinolfi, A. Aduszkiewicz, Z. Ahmad, J. Ahmed, T. Alion, S. Alonso Monsalve, M. Alrashed, C. Alt, A. Alton, P. Amedo, J. Anderson, C. Andreopoulos, M. P. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antonova, S. Antusch, A. Aranda-Fernandez, A. Ariga, L. O. Arnold, M. A. Arroyave, J. Asaadi, A. Aurisano, V. Aushev, D. Autiero, M. Ayala-Torres, F. Azfar, A. Back, H. Back, J. J. Back, C. Backhouse, P. Baesso, I. Bagaturia, L. Bagby, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, G. J. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, E. Belchior, J. B. R. Battat, F. Battisti, F. Bay, J. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, D. Belver, N. Benekos, F. Bento Neves, S. Berkman, P. Bernardini, R. M. Berner, H. Berns, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, M. Bhattacharjee, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. D. M. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, M. Bongrand, F. Bonini, A. Booth, C. Booth, S. Bordoni, A. Borkum, T. Boschi, N. Bostan, P. Bour, C. Bourgeois, S. B. Boyd, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Brandt, J. Bremer, C. Brew, E. Brianne, S. J. Brice, C. Brizzolari, C. Bromberg, G. Brooijmans, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, I. Cagnoli, D. Caiulo, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, A. Caminata, M. Campanelli, K. Cankocak, D. Caratelli, G. Carini, B. Carlus, P. Carniti, I. Caro Terrazas, H. Carranza, T. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, E. Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, H. Chen, M. Chen, Y. Chen, Z. Chen, D. Cherdack, C. Chi, S. Childress, A. Chiriacescu, G. Chisnall, K. Cho, S. Choate, D. Chokheli, S. Choubey, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, E. Church, V. Cicero, P. Clarke, T. E. Coan, A. G. Cocco, J. A. B. Coelho, E. Conley, R. Conley, J. M. Conrad, M. Convery, S. Copello, L. Corwin, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, E. Cristaldo, R. Cross, A. Cudd, C. Cuesta, Y. Cui, D. Cussans, M. Dabrowski, O. Dalager, H. da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, R. M. De Almeida, P. Debbins, I. De Bonis, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, P. De Lurgio, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. W. Deptuch, A. 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Mishra, A. Mislivec, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, A. Montanari, C. Montanari, D. Montanari, E. Montagna, L. M. Montano Zetina, J. Moon, M. Mooney, A. F. Moor, D. Moreno, C. Morris, C. Mossey, E. Motuk, C. A. Moura, J. Mousseau, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, D. Munford, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, D. Navas-Nicolás, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, D. Newhart, H. Newton, M. Niccolo, R. Nichol, F. Nicolas-Arnaldos, M. Nicoletta, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, J. P. Ochoa-Ricoux, A. Olivares Del Campo, A. Olivier, A. Olshevskiy, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, S. Pakvasa, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, J. L. Palomino-Gallo, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. J. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. M. Peeters, E. Pennacchio, A. Penzo, O. L. G. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, F. Piastra, L. Pickering, F. Pietropaolo, R. Plunkett, R. Poling, X. Pons, N. Poonthottathil, F. Poppi, S. Pordes, J. Porter, M. Potekhin, R. Potenza, B. V. K. S. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, S. Prince, D. Pugnere, X. Qian, M. C. Queiroga Bazetto, J. L. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, A. Rakotonandrasana, L. Rakotondravohitra, Y. A. Ramachers, R. Rameika, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Raut, R. F. Razakamiandra, J. S. Real, B. Rebel, M. Reggiani-Guzzo, T. Rehak, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, A. Renshaw, S. Rescia, F. Resnati, A. Reynolds, C. Riccio, G. Riccobene, L. C. J. Rice, J. Ricol, A. Rigamonti, Y. Rigaut, D. Rivera, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, E. Rodriguez Bonilla, J. Rodriguez Rondon, S. Rosauro-Alcaraz, M. Rosenberg, P. Rosier, B. Roskovec, M. Rossella, J. Rout, P. Roy, S. Roy, A. Rubbia, C. Rubbia, F. C. Rubio, B. Russell, D. Ruterbories, R. Saakyan, S. Sacerdoti, T. Safford, R. Sahay, N. Sahu, P. Sala, N. Samios, O. Samoylov, M. C. Sanchez, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schaffer, H. Schellman, P. Schlabach, D. Schmitz, K. Scholberg, A. Schukraft, E. Segreto, J. Sensenig, I. Seong, A. Sergi, D. Sgalaberna, M. H. Shaevitz, S. 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Teklu, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, A. Thea, J. L. Thompson, C. Thorn, S. C. Timm, J. Todd, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, D. Totani, M. Toups, C. Touramanis, N. Tosi, R. Travaglini, J. Trevor, S. Trilov, W. H. Trzaska, Y. T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, M. A. Uchida, J. Urheim, T. Usher, S. Uzunyan, M. R. Vagins, P. Vahle, G. A. Valdiviesso, E. Valencia, P. Valerio, Z. Vallari, J. W. F. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, F. Varanini, D. Vargas, G. Varner, J. Vasel, S. Vasina, G. Vasseur, N. Vaughan, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, H. Wang, J. Wang, L. Wang, M. H. L. S. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, J. Wolcott, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, C. Wret, W. Wu, Y. Xiao, E. Yandel, G. Yang, K. Yang, S. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, T. Young, B. Yu, H. Yu, J. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. Zeit, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, M. Zhao, E. Zhivun, G. Zhu, P. Zilberman, E. D. Zimmerman, M. Zito, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and On behalf of the DUNE Collaboration
Subjects: neutrino, near detector, neutrino oscillations, Deep Underground Neutrino Experiment, DUNE, Physics, QC1-999, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents.
Published: 2021
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