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51. Adoption and Effects of Software Engineering Best Practices in Machine Learning

Author

Serban, Alex, van der Blom, Koen, Hoos, Holger, and Visser, Joost

Subjects
Computer Science - Software Engineering
Abstract

The increasing reliance on applications with machine learning (ML) components calls for mature engineering techniques that ensure these are built in a robust and future-proof manner. We aim to empirically determine the state of the art in how teams develop, deploy and maintain software with ML components. We mined both academic and grey literature and identified 29 engineering best practices for ML applications. We conducted a survey among 313 practitioners to determine the degree of adoption for these practices and to validate their perceived effects. Using the survey responses, we quantified practice adoption, differentiated along demographic characteristics, such as geography or team size. We also tested correlations and investigated linear and non-linear relationships between practices and their perceived effect using various statistical models. Our findings indicate, for example, that larger teams tend to adopt more practices, and that traditional software engineering practices tend to have lower adoption than ML specific practices. Also, the statistical models can accurately predict perceived effects such as agility, software quality and traceability, from the degree of adoption for specific sets of practices. Combining practice adoption rates with practice importance, as revealed by statistical models, we identify practices that are important but have low adoption, as well as practices that are widely adopted but are less important for the effects we studied. Overall, our survey and the analysis of responses received provide a quantitative basis for assessment and step-wise improvement of practice adoption by ML teams., Comment: Accepted and published at the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) 2020

Published
2020
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52. Automated Configuration of Negotiation Strategies

Author

Renting, Bram M., Hoos, Holger H., and Jonker, Catholijn M.

Subjects
Computer Science - Multiagent Systems, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Bidding and acceptance strategies have a substantial impact on the outcome of negotiations in scenarios with linear additive and nonlinear utility functions. Over the years, it has become clear that there is no single best strategy for all negotiation settings, yet many fixed strategies are still being developed. We envision a shift in the strategy design question from: What is a good strategy?, towards: What could be a good strategy? For this purpose, we developed a method leveraging automated algorithm configuration to find the best strategies for a specific set of negotiation settings. By empowering automated negotiating agents using automated algorithm configuration, we obtain a flexible negotiation agent that can be configured automatically for a rich space of opponents and negotiation scenarios. To critically assess our approach, the agent was tested in an ANAC-like bilateral automated negotiation tournament setting against past competitors. We show that our automatically configured agent outperforms all other agents, with a 5.1% increase in negotiation payoff compared to the next-best agent. We note that without our agent in the tournament, the top-ranked agent wins by a margin of only 0.01%., Comment: Appears in Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020)

Published
2020

53. Improving the Performance of Stochastic Local Search for Maximum Vertex Weight Clique Problem Using Programming by Optimization

Author

Chu, Yi, Luo, Chuan, Hoos, Holger H., Lin, QIngwei, and You, Haihang

Subjects
Computer Science - Artificial Intelligence
Abstract

The maximum vertex weight clique problem (MVWCP) is an important generalization of the maximum clique problem (MCP) that has a wide range of real-world applications. In situations where rigorous guarantees regarding the optimality of solutions are not required, MVWCP is usually solved using stochastic local search (SLS) algorithms, which also define the state of the art for solving this problem. However, there is no single SLS algorithm which gives the best performance across all classes of MVWCP instances, and it is challenging to effectively identify the most suitable algorithm for each class of MVWCP instances. In this work, we follow the paradigm of Programming by Optimization (PbO) to develop a new, flexible and highly parametric SLS framework for solving MVWCP, combining, for the first time, a broad range of effective heuristic mechanisms. By automatically configuring this PbO-MWC framework, we achieve substantial advances in the state-of-the-art in solving MVWCP over a broad range of prominent benchmarks, including two derived from real-world applications in transplantation medicine (kidney exchange) and assessment of research excellence.

Published
2020

56. Daily energy expenditure through the human life course

Author

Pontzer, Herman, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issaad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan G, Close, Graeme L, Cooper, Jamie A, Cooper, Richard, Das, Sai Krupa, Dugas, Lara R, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, Hamdouchi, Asmaa El, Hoos, Marjije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Teresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia, Luke, Amy H, Rood, Jennifer, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, Speakman, John R, and Consortium§, IAEA DLW Database

Subjects
Aging, Nutrition, Adolescent, Adult, Aged, Aged, 80 and over, Basal Metabolism, Body Composition, Body Weight, Child, Child, Preschool, Energy Metabolism, Exercise, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Pregnancy, Young Adult, IAEA DLW Database Consortium, General Science & Technology
Abstract

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Published
2021

58. Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review.

Author

Kenner, Barbara, Chari, Suresh T, Kelsen, David, Klimstra, David S, Pandol, Stephen J, Rosenthal, Michael, Rustgi, Anil K, Taylor, James A, Yala, Adam, Abul-Husn, Noura, Andersen, Dana K, Bernstein, David, Brunak, Søren, Canto, Marcia Irene, Eldar, Yonina C, Fishman, Elliot K, Fleshman, Julie, Go, Vay Liang W, Holt, Jane M, Field, Bruce, Goldberg, Ann, Hoos, William, Iacobuzio-Donahue, Christine, Li, Debiao, Lidgard, Graham, Maitra, Anirban, Matrisian, Lynn M, Poblete, Sung, Rothschild, Laura, Sander, Chris, Schwartz, Lawrence H, Shalit, Uri, Srivastava, Sudhir, and Wolpin, Brian

Subjects
Humans, Carcinoma, Pancreatic Ductal, Pancreatic Neoplasms, Prognosis, Survival Analysis, Interdisciplinary Communication, Genomics, Artificial Intelligence, Early Detection of Cancer, Biomarkers, Tumor, Cancer, Rare Diseases, Prevention, Pancreatic Cancer, Digestive Diseases, Good Health and Well Being, artificial intelligence, machine learning, pancreatic cancer, early detection, Clinical Sciences, Gastroenterology & Hepatology
Abstract

AbstractDespite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit (www.pdac-virtualsummit.org) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer-Current Efforts; Collaborative Opportunities; and Moving Forward-Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

Published
2021

59. A standard calculation methodology for human doubly labeled water studies.

Author

Speakman, John R, Yamada, Yosuke, Sagayama, Hiroyuki, Berman, Elena SF, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issaad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan GJA, Close, Graeme L, Cooper, Jamie A, Creasy, Seth A, Das, Sai Krupa, Cooper, Richard, Dugas, Lara R, Ebbeling, Cara B, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, El Hamdouchi, Asmaa, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Ludwig, David S, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia U, Melanson, Edward L, Luke, Amy H, Pontzer, Herman, Rood, Jennifer, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, and IAEA DLW database group

Subjects
IAEA DLW database group, doubly labeled water, free-living, total energy expenditure, validation
Abstract

The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (

Published
2021

63. What is the aetiology of dysnatraemia in COVID-19 and how is this related to outcomes in patients admitted during earlier and later COVID-19 waves? A multicentre, retrospective observational study in 11 Dutch hospitals

Author

Babette Verkouteren, Dan Piña-Fuentes, Martijn Beudel, Thomas Ludden, Rik H G Olde Engberink, Tom Dormans, Martijn D de Kruif, Suat Simsek, Joop P van den Bergh, Hazra Moeniralam, Renee Douma, Kees Brinkman, Wouter Hinsenveld, Lucas Ramos, Anne Pirson, Deborah Hubers, Shi Hu, Rajat Thomas, Michiel Schinkel, Caroline E Wyers, Daisy Rusch, Lianne de Haan, Niels C Gritters van den Oever, Nienke Paternotte, Robert-Jan Goldhoorn, Brent Appelman, Esther Lems, Marije ten Wolde, Esther K Haspels-Hogervorst, Neyma Bokhizzou, Niels Gritters van den Oever, Joop van den Bergh, Martijn de Kruif, Helen Leavis, Derk Arts, Nick Nurmohamed, Rens Reeskamp, Willem Herter, Bas Vonk, Ricardo Lopes, Deborah Huberts, Marije Wolfers, Sander de Kuij, Sophie Noordzij, Sibbeliene van den Bosch, Benthe Verhoef, Michele Methorst, Shahan Darwesh, Tijn van Egmond, Gulsum Nasim, Hamza Ali, Lars de Boer, Myrthe Nagel, Maud Koenis, Agnetha Bijlsma, Britt Balvers, Isabella Ghauharali, Jelle de Jongh, Maira Emanuel, Nisrine Aynaou, Rosemarie de Ridder, Insaff Darraz, Oumaima Darraz, Alanar Cinar, Jesse Roosen, Larissa Heideman, Asabi Leliveld, Dana Ruijter, Neeltje Rosenberg, Djoeke Woutman, Tom Vermeulen, Sam de Joode, Willem Berger, Ozgu Varan, Soesja Pinto, Sientje Sluis, Bibi Kuiper, Tim van der Putten, Dominique Bosje, Mahunda Sinyangwe, Roos van Rhijn, Koen Kruif, Miriam den Heijer, Koen de Kruijf, Sam Hofhuis, Gwendolyn Telting, Susan van der Lei, Pien van Paassen, Emil ter Veer, Krijna Opschoor, Camille Breukhoven, Florine Jiwa, Peter de Gooyer, Jan Vrijdag, Stans van Gelder, Anne Pannekoek, Laura Dommershuijzen, Estelle Adang, Maud van Maren, Isabel Koop, Bart Sanders, Joukje Wanten, Dax Trommelen, Fleur Smeets, Kyra Heuvelings, Maud Cox, Milou Rademaekers, Vivian Hendrikx, Ilona van Rooij, Wendy Heuts, Laura Oudeman, Evelien Brans, Karin Slot, Kirsten Boerma-Argelo, Wilma Kok, Lieke Harmsen, Ingrid Boerema, Anne Raafs, Anne Smaal, Bibiane Pop, Carmen Waterink, Casper Vrij, Daphne van der Willik, Frederic Reitsma, Imogene Pieters, Jade Logger, Laura Sijben, Maikel Peeters, Mariël Teunissen, Marije Blok-Hoos, Marjolein Ketels, Michiel Henkens, Mireille Spanjers, Monique Jacob-Dols, Patrick de Hoogt, Rik Houben, Roos van Gorp, and Josien Jansen

Subjects
Medicine
Abstract

Objectives To evaluate the relationship among dysnatraemia at hospital presentation and duration of admission, risk of intensive care unit (ICU) admission and all-cause mortality and to assess the underlying pathophysiological mechanism of hyponatraemia in patients with COVID-19. Our hypothesis is that both hyponatraemia and hypernatraemia at presentation are associated with adverse outcomes.Design Observational study.Setting Secondary care; 11 Dutch hospitals (2 university and 9 general hospitals).Participants An analysis was performed within the retrospective multicentre cohort study COVIDPredict. 7811 patients were included (60% men, 40% women) between 24 February 2020 and 9 August 2022. Patients who were ≥18 years with PCR-confirmed COVID-19 or CT with COVID-19 reporting and data system score≥4 and alternative diagnosis were included. Patients were excluded when serum sodium levels at presentation were not registered in the database or when they had been transferred from another participating hospital.Outcome measures We studied demographics, medical history, symptoms and outcomes. Patients were stratified according to serum sodium concentration and urinary sodium excretion.Results Hyponatraemia was present in 2677 (34.2%) patients and hypernatraemia in 126 (1.6%) patients. Patients with hyponatraemia presented more frequently with diarrhoea, lower blood pressure and tachycardia. Hyponatraemia was, despite a higher risk for ICU admission (OR 1.27 (1.11–1.46; p

Published
2023
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64. Trends in HIV prevalence, incidence, and progress towards the UNAIDS 95-95-95 targets in Malawi among individuals aged 15–64 years: population-based HIV impact assessments, 2015−16 and 2020−21

Author

Mwansambo, Charles, Kalua, Thokozani, Kagoli, Mathews, Mvula, Bernard, Kanyuka, Mercy, Ndawala, Jameson, Chirwa, Isaac, Matatiyo, Blackson, Yavo, Daniel, Patel, Hetal, Parekh, Bharat, El-Sadr, Wafaa, Chege, Duncan, Radin, Elizabeth, Hoos, David, Low, Andrea, Gummerson, Elizabeth, Payne, Danielle, Wadonda-Kabondo, Nellie, Wang, Alice, Smith-Sreen, Joshua, Kabaghe, Alinune, Bello, George, Kayigamba, Felix, Tenthani, Lyson, Maida, Alice, Auld, Andrew, Voetsch, Andrew C, Jonnalagadda, Sasi, Brown, Kristin, West, Christine A, Kim, Evelyn, Ogollah, Francis, Farahani, Mansoor, Dobbs, Trudy, Jahn, Andreas, Mirkovic, Kelsey, and Nyirenda, Rose

Published
2023
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68. Space and Artificial Intelligence (Dagstuhl Seminar 23461)

Author

Sašo Džeroski and Holger H. Hoos and Bertrand Le Saux and Leendert van der Torre and Ana Kostovska, Džeroski, Sašo, Hoos, Holger H., Le Saux, Bertrand, van der Torre, Leendert, Kostovska, Ana, Sašo Džeroski and Holger H. Hoos and Bertrand Le Saux and Leendert van der Torre and Ana Kostovska, Džeroski, Sašo, Hoos, Holger H., Le Saux, Bertrand, van der Torre, Leendert, and Kostovska, Ana

Abstract

This report documents the program and the outcomes of the Dagstuhl Seminar 23461 "Space and Artificial Intelligence". The seminar was interdisciplinary, situated at the intersection of research on AI / computer science and space research. Since each of these is a very wide field on its own, we focussed on a selection of topics from each of the two and their intersections. On the artificial intelligence side, we focused on data-driven AI, which makes use of data in order to produce intelligent behaviour and notably includes machine learning approaches. We also considered knowledge-based AI, which is focussed on the explicit formalisation of human knowledge and its use for tasks such as reasoning, planning, and scheduling. On the space research side, we considered the two major branches of space operations (SO) and Earth observation (EO). The seminar brought together a diverse set of players, including researchers from academia, on one hand, and practitioners from space agencies (ESA, NASA) and industry, on the other hand. The seminar included plenary talks and parallel group discussions. Through the plenary talks, we obtained insight into the state-of-the-art in the different areas of AI research and space research, and especially in their intersections. Through the parallel group discussions, we identified obstacles and challenges to further progress and charted directions for further work.

Published
2024
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84. Topical glucocorticoid application causing iatrogenic Cushing’s syndrome followed by secondary adrenal insufficiency in infants: two case reports

Author

Nicola Matejek, Johannes Hoos, Paul Martin Holterhus, Markus Bettendorf, and Daniela Choukair

Subjects
Topical glucocorticoid application, Iatrogenic Cushing’s disease, Dexamethasone eye drops, Topical application of clobetasol, Medicine
Abstract

Abstract Background Iatrogenic Cushing’s syndrome induced by oral and parenteral glucocorticoid administration is a well-known complication. Immediate withdrawal from exogenous steroids can lead to life-threatening adrenal insufficiency. However, Cushing’s syndrome caused by topical treatment with glucocorticoids, such as dexamethasone eye drops or dermal application, is rarely recognized. Young infants in particular are at high risk of suffering from iatrogenic Cushing’s syndrome when treated with highly potent topical glucocorticoids. Case presentation We present a 6-month-old Syrian boy with cushingoid face after dermal clobetasol cream treatment and a 2-year-old Iranian girl with severe growth retardation after application of dexamethasone eye drops. Both families have a migration background and language barriers. In both cases no endogenous cortisol secretion was initially detected in serum and in 24-hour collected urine. After dose reduction of glucocorticoids, severity of symptoms was reversible and serum cortisol was detectable. Discussion and conclusion Young infants are at high risk of developing Cushing’s syndrome from topically applied highly potent glucocorticoids. Precise recommendations of treatment dosage, duration, and frequency must be given to the parents, and if necessary, with the help of an interpreter. Monitoring of height and weight as well as regular pediatric follow-ups should be scheduled. Physicians should be aware of potential adrenal insufficiency following withdrawal from long-term topical glucocorticoid treatment, and hydrocortisone treatment should be considered.

Published
2022
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87. Automated Algorithm Selection: Survey and Perspectives

Author

Kerschke, Pascal, Hoos, Holger H., Neumann, Frank, and Trautmann, Heike

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms. This is particularly pronounced for computationally hard problems, where in most cases, no single algorithm defines the state of the art; instead, there is a set of algorithms with complementary strengths. This performance complementarity can be exploited in various ways, one of which is based on the idea of selecting, from a set of given algorithms, for each problem instance to be solved the one expected to perform best. The task of automatically selecting an algorithm from a given set is known as the per-instance algorithm selection problem and has been intensely studied over the past 15 years, leading to major improvements in the state of the art in solving a growing number of discrete combinatorial problems, including propositional satisfiability and AI planning. Per-instance algorithm selection also shows much promise for boosting performance in solving continuous and mixed discrete/continuous optimisation problems. This survey provides an overview of research in automated algorithm selection, ranging from early and seminal works to recent and promising application areas. Different from earlier work, it covers applications to discrete and continuous problems, and discusses algorithm selection in context with conceptually related approaches, such as algorithm configuration, scheduling or portfolio selection. Since informative and cheaply computable problem instance features provide the basis for effective per-instance algorithm selection systems, we also provide an overview of such features for discrete and continuous problems. Finally, we provide perspectives on future work in the area and discuss a number of open research challenges., Comment: This is the author's final version, and the article has been accepted for publication in Evolutionary Computation

Published
2018

88. Dynamics and structural changes of calmodulin upon interaction with the antagonist calmidazolium

Author

Corentin Léger, Irène Pitard, Mirko Sadi, Nicolas Carvalho, Sébastien Brier, Ariel Mechaly, Dorothée Raoux-Barbot, Maryline Davi, Sylviane Hoos, Patrick Weber, Patrice Vachette, Dominique Durand, Ahmed Haouz, J. Iñaki Guijarro, Daniel Ladant, and Alexandre Chenal

Subjects
Calmodulin, CaM, Calmidazolium, CDZ, Calmodulin antagonist, Structure, Biology (General), QH301-705.5
Abstract

Abstract Background Calmodulin (CaM) is an evolutionarily conserved eukaryotic multifunctional protein that functions as the major sensor of intracellular calcium signaling. Its calcium-modulated function regulates the activity of numerous effector proteins involved in a variety of physiological processes in diverse organs, from proliferation and apoptosis, to memory and immune responses. Due to the pleiotropic roles of CaM in normal and pathological cell functions, CaM antagonists are needed for fundamental studies as well as for potential therapeutic applications. Calmidazolium (CDZ) is a potent small molecule antagonist of CaM and one the most widely used inhibitors of CaM in cell biology. Yet, CDZ, as all other CaM antagonists described thus far, also affects additional cellular targets and its lack of selectivity hinders its application for dissecting calcium/CaM signaling. A better understanding of CaM:CDZ interaction is key to design analogs with improved selectivity. Here, we report a molecular characterization of CaM:CDZ complexes using an integrative structural biology approach combining SEC-SAXS, X-ray crystallography, HDX-MS, and NMR. Results We provide evidence that binding of a single molecule of CDZ induces an open-to-closed conformational reorientation of the two domains of CaM and results in a strong stabilization of its structural elements associated with a reduction of protein dynamics over a large time range. These CDZ-triggered CaM changes mimic those induced by CaM-binding peptides derived from physiological protein targets, despite their distinct chemical natures. CaM residues in close contact with CDZ and involved in the stabilization of the CaM:CDZ complex have been identified. Conclusion Our results provide molecular insights into CDZ-induced dynamics and structural changes of CaM leading to its inhibition and open the way to the rational design of more selective CaM antagonists. Graphical abstract Calmidazolium is a potent and widely used inhibitor of calmodulin, a major mediator of calcium-signaling in eukaryotic cells. Structural characterization of calmidazolium-binding to calmodulin reveals that it triggers open-to-closed conformational changes similar to those induced by calmodulin-binding peptides derived from enzyme targets. These results provide molecular insights into CDZ-induced dynamics and structural changes of CaM leading to its inhibition and open the way to the rational design of more selective CaM antagonists.

Published
2022
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91. From fear to action: AI governance and opportunities for all

Author

Kevin Baum, Joanna Bryson, Frank Dignum, Virginia Dignum, Marko Grobelnik, Holger Hoos, Morten Irgens, Paul Lukowicz, Catelijne Muller, Francesca Rossi, John Shawe-Taylor, Andreas Theodorou, and Ricardo Vinuesa

Subjects
Artificial Intelligence, governance, responsible AI, Trustworthy AI, large language models, generative AI, Electronic computers. Computer science, QA75.5-76.95
Published
2023
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92. 'The Ability to Lay Yourself Bare': Centering Rupture, Inherited Conversations, and Vulnerability in Professional Development

Author

Mendoza, Elizabeth, Hand, Victoria, van Es, Elizabeth A., Hoos, Shannon, and Frierson, Michelle

Abstract

A dominant paradigm for research on teacher professional development has centred teacher learning as created in and through practice. Critical scholars argue for the need to grapple productively with the complexities of teaching in the power-laden contexts of schooling. This involves continual reflection on the ways that teaching reinforces structural inequalities. We articulate the notion of historical self to describe noticing as ground in both personal and social histories that are situated in hierarchies of power and dominant ideologies. We draw on data from a three year, multi-site project that engaged teachers, community members, and researchers in co-developing a noticing for re-humanising framework. Through the narrative of Shannon, a project participant-researcher, we illuminate as part of the historical self: (1) the interconnectedness of both personal and social histories in and through moment-to-moment interactions and their relation to what and how we notice; (2) the vulnerability embedded in rupturing embedded assumptions in these histories, and (3) the importance of understanding what we do "not" notice, as tied to our privilege.

Published
2021
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93. Human total, basal and activity energy expenditures are independent of ambient environmental temperature

Author

Andersen, Lene F., Anderson, Liam J., Arab, Lenore, Baddou, Issad, Addo, Bedu, Blanc, Stephane, Bonomi, Alberto, Bouten, Carlijn V.C., Bovet, Pascal, Branth, Stefan, De Bruin, Niels C., Butte, Nancy F., Colbert, Lisa H., Camps, Stephan G., Dutman, Alice E., Eaton, Simon D., Ekelund, Ulf, Entringer, Sonja, Ebbeling, Cara, Elmståhl, Sölve, Fogelholm, Mikael, Forrester, Terrence, Fudge, Barry W., Harris, Tamara, Heijligenberg, Rik, Goris, Annelies H., Hambly, Catherine, Hoos, Marije B., Jorgensen, Hans U., Joosen, Annemiek M., Kempen, Kitty P., Kimura, Misaka, Kriengsinyos, Watanee, Lambert, Estelle V., Larsson, Christel L., Lessan, Nader, Ludwig, David S., McCloskey, Margaret, Medin, Anine C., Meijer, Gerwin A., Matsiko, Eric, Melse-Boonstra, Alida, Morehen, James C., Morton, James P., Nicklas, Theresa A., Pannemans, Daphne L., Pietiläinen, Kirsi H., Philippaerts, Renaat M., Rabinovich, Roberto A., Reilly, John J., Rothenberg, Elisabet M., Schuit, Albertine J., Schulz, Sabine, Sjödin, Anders M., Subar, Amy, Tanskanen, Minna, Uauy, Ricardo, Valenti, Giulio, Van Etten, Ludo M., Berg-Emons, Rita Van den, Van Gemert, Wim G., Velthuis-te Wierik, Erica J., Verboeket-van de Venne, Wilhelmine W., Verbunt, Jeanine A., Wells, Jonathan C.K., Wilson, George, Zhang, Xueying, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N., Blaak, Ellen E., Buchowski, Maciej S., Close, Graeme L., Cooper, Jamie A., Das, Sai Krupa, Dugas, Lara R., Gurven, Michael, El Hamdouchi, Asmaa, Hu, Sumei, Joonas, Noorjehan, Katzmarzyk, Peter, Kraus, William E., Kushner, Robert F., Leonard, William R., Martin, Corby K., Meijer, Erwin P., Neuhouser, Marian L., Ojiambo, Robert M., Pitsiladis, Yannis P., Plasqui, Guy, Prentice, Ross L., Racette, Susan B., Ravussin, Eric, Redman, Leanne M., Reynolds, Rebecca M., Roberts, Susan B., Sardinha, Luis B., Silva, Analiza M., Stice, Eric, Urlacher, Samuel S., Van Mil, Edgar A., Wood, Brian M., Murphy-Alford, Alexia J., Loechl, Cornelia, Luke, Amy H., Rood, Jennifer, Schoeller, Dale A., Westerterp, Klaas R., Wong, William W., Pontzer, Herman, and Speakman, John R.

Published
2022
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