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Fluctuating temperature modifies heat-mortality association around the globe

The Innovation 2022年第2期3卷 65-72页

作者： Yao Wu Bo Wen Shanshan Li Antonio Gasparrini Shilu Tong Ala Overcenco Ales Urban Alexandra Schneider Alireza Entezari Ana Maria Vicedo-Cabrera Antonella Zanobetti Antonis Analitis Ariana Zeka Aurelio Tobias Barrak Alahmad Ben Armstrong Bertil Forsberg CarmenÍñiguez Caroline Ameling César De la Cruz Valencia ChristoferÅström Danny Houthuijs Do Van Dung Dominic Royé Ene Indermitte Eric Lavigne Fatemeh Mayvaneh Fiorella Acquaotta Francesca de’Donato Francesco Sera Gabriel Carrasco-Escobar Haidong Kan Hans Orru Ho Kim Iulian-Horia Holobaca Jan Kyselý Joana Madureira Joel Schwartz Klea Katsouyanni Magali Hurtado-Diaz Martina SRagettli Masahiro Hashizume Mathilde Pascal Micheline de Sousa Zanotti Stagliorio Coélho Noah Scovronick Paola Michelozzi Patrick Goodman Paulo Hilario Nascimento Saldiva Rosana Abrutzky Samuel Osorio Tran Ngoc Dang Valentina Colistro Veronika Huber Whanhee Lee Xerxes Seposo Yasushi Honda Michelle L.Bell Yuming Guo Department of Epidemiology and Preventive Medicine School of Public Health and Preventive MedicineMonash UniversityMelbourne 3004Australia Climate Air Quality Research UnitSchool of Public Health and Preventive MedicineMonash UniversityMelbourne 3004Australia Department of Public Health Environments and SocietyLondon School of Hygiene&Tropical MedicineLondon WC1E 7HTUK Centre for Statistical Methodology London School of Hygiene&Tropical MedicineLondon WC1E 7HTUK Centre on Climate Change&Planetary Health London School of Hygiene&Tropical MedicineLondon WC1E 7HTUK Shanghai Children’s Medical Centre Shanghai Jiao Tong UniversityShanghai 200025China School of Public Health Institute of Environment and Human HealthAnhui Medical UniversityHefei 230032China Center for Global Health Nanjing Medical UniversityNanjing 211166China School of Public Health and Social Work Queensland University of TechnologyBrisbane 4000Australia National Agency for Public Health of the Ministry of Health Labour and Social Protection of the Republic of MoldovaChisinau MD-2009Republic of Moldova Institute of Atmospheric Physics Czech Academy of SciencesPrague 14100Czech Republic Faculty of Environmental Sciences Czech University of Life SciencesPrague 16500Czech Republic Institute of Epidemiology Helmholtz Zentrum M€unchen-German Research Center for Environmental HealthNeuherberg 85747Germany Faculty of Geography and Environmental Sciences Hakim Sabzevari UniversitySabzevar ***Iran Institute of Social and Preventive Medicine University of BernBern 3012Switzerland Oeschger Center for Climate Change Research University of BernBern 3012Switzerland Department of Environmental Health Harvard T.H.Chan School of Public HealthHarvard UniversityBostonMA 02115USA Department of Hygiene Epidemiology and Medical StatisticsNational and Kapodistrian University of AthensAthens 11527Greece Institute for Environment Healthand SocietiesBrunel University LondonLondon UB83PNUK Institute of Environmental Assessment and

Studies have investigated the effects of heat and temperature variability(TV)on ***,few assessed whether TV modifies the heat-mortality *** on daily temperature and mortality in the warm season were collected from 717 locations across 36 *** was calculated as the standard deviation of the average of the same and previous days’minimum and maximum temperatures.

关键词： deviation modif heat

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A General and Flexible Search Framework for Disassembly Planning

A General and Flexible Search Framework for Disassembly Plan...

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IEEE International Conference on Robotics and Automation

作者： Timothy Ebinger Sascha Kaden Shawna Thomas Robert Andre Nancy M. Amato Ulrike Thomas Member of the Department of Computer Science & Engineering Texas A&M University TX USA Member of the Robotics and Human Machine Interaction Group Chemnitz University of Technology Chemnitz Germany

We present a new general framework for disassembly sequence planning. This framework is versatile allowing different types of search schemes (exhaustive vs. preemptive), various part separation techniques, and the ability to group parts, or not, into subassemblies to improve the solution efficiency and parallelism. This enables a truly hierarchical approach to disassembly sequence planning. We demonstrate two different search strategies using this framework that can either yield a single solution quickly or provide a spectrum of solutions from which an optimal may be selected. We also develop a method for subassembly identification based on collision information. Our results show improved performance over an iterative motion planning based method for finding a single solution and greater functionality through hierarchical planning and optimal solution search.

关键词： Planning Trajectory Measurement Data structures Search problems Learning systems Containers

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Not just functional, nutritious, but also experiential: Designing eating experiences for space travel 69

Not just functional, nutritious, but also experiential: Desi...

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69th International Astronautical Congress: #InvolvingEveryone, IAC 2018

作者： Obrist, Marianna Tu, Yunwen Yao, Lining Velasco, Carlos Sussex Computer Human Interaction Lab School of Engineering and Informatics University of Sussex Chichester 1 BrightonBN1 9QJ United Kingdom Food Design 322 Crestview Circle Daly CityCA United States Carnegie Mellon University School of Computer Science 5000 Forbes Ave PittsburghPA15213 United States Center for Multisensory Marketing Department of Marketing BI Norwegian Business School Nydalsveien 37 Oslo0484 Norway

In light of short- and long-term space travels to the Moon and Mars, it is essential to design nutritious foods, but also to make eating an enjoyable experience. To date, though, most research on space food design emphasizes the functional and nutritional aspects of food, but there are no systematic studies that focus is on the human experience of eating in space. We know however that food has a multi-dimensional and multisensorial role in societies and that sensory, hedonic, and social features of eating and food design should not be underestimated. We present, how research in the field of human-computer interaction (HCI) can provide a user-centered design approach to co-create innovative ideas around the future of food and eating in space, balancing functional and experiential factors. Based on our research and inspired by advances in human food-interaction design, we developed three design concepts that integrate and tackle four crucial challenges for 'Eating in Space': to be functional, sensorial, emotional, and social. Moreover, we consider the environmental/atmospheric perspective in our design concepts. We can particularly capitalize on recent technological advances around digital fabrication, food 3D printing technology, and virtual and augmented reality to enable the design and integration of multisensory eating experiences. We also highlight that in future space travels, the target users will diversify. Thinking about future target users, we need to look at astronauts (current users, paid to do the job) but also beyond and consider paying customers (non-astronauts) who will be able to book a space holiday to the Moon or Mars. To create the right conditions for space travelling and to satisfy those users, we need to innovate beyond the initial excitement of designing an 'eating like an astronaut' experience and design for experiences beyond the novelty of the situation. To do so we can draw upon prior HCI research in human food-interaction design and build

关键词： human computer interaction

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Small P values may not yield robust findings:an example using REST-meta-PD

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science Bulletin 2021年第21期66卷 2148-2152,M0003页

作者： Xi-Ze Jia Na Zhao Hao-Ming Dong Jia-Wei Sun Marek Barton Roxana Burciu Nicolas Carrière Antonio Cerasa Bo-Yu Chen Jun Chen Stephen Coombes Luc Defebvre Christine Delmaire Kathy Dujardin Fabrizio Esposito Guo-Guang Fan Federica Di Nardo Yi-Xuan Feng Brett W.Fling Saurabh Garg Moran Gilat Martin Gorges Shu-Leong Ho Fay BHorak Xiao Hu Xiao-Fei Hu Biao Huang Pei-Yu Huang Ze-Juan Jia Christina Jones Jan Kassubek Lenka Krajcovicova Ajay Kurani Jing Li Qing Li Ai-Ping Liu Bo Liu Hu Liu Wei-Guo Liu Renaud Lopes Yu-Ting Lou Wei Luo Tara Madhyastha Ni-Ni Mao Grainne McAlonan Martin J.McKeown Shirley Pang Andrea Quattrone Irena Rektorova Alessia Sarica Hui-Fang Shang James M.Shine Priyank Shukla Tomas Slavicek Xiao-Peng Song Gioacchino Tedeschi Alessandro Tessitore David Vaillancourt Jian Wang Jue Wang Z.Jane Wang Lu-Qing Wei Xia Wu Xiao-Jun Xu Lei Yan Jing Yang Wan-Qun Yang Nai-Lin Yao De-Long Zhang Jiu-Quan Zhang Min-Ming Zhang Yan-Ling Zhang Cai-Hong Zhou Chao-Gan Yan Xi-Nian Zuo Mark Hallett Tao Wu Yu-Feng Zang Center for Cognition and Brain Disorders the Affiliated HospitalHangzhou Normal UniversityHangzhou 310015China Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments Hangzhou 311121China National Basic Science Data Center Beijing 100190China State Key Laboratory of Cognitive Neuroscience and Learning&McGovern Institute for Brain Research Beijing Normal UniversityBeijing 100875China School of Information and Electronics Technology Jiamusi UniversityJiamusi 154007China Neuroscience Program Central European Institute of TechnologyCEITECMasaryk UniversityBrno 62500Czech Republic Department of Applied Physiology and Kinesiology University of FloridaGainesville FL 32611USA Univ.Lille InsermCHU LilleU1172-LilNCog-Lille Neuroscience&CognitionLille F-59000France The Institute for Biomedical Research and Innovation National Research CouncilMangone CS 87050Italy Department of Radiology The First Affiliated Hospital of China Medical UniversityShenyang 110001China Department of Radiology Guangdong Provincial Hospital of Chinese MedicineGuangzhou 510120China Department of Medicine Surgery and DentistryScuola Medica SalernitanaUniversity of SalernoFiscianoSA 132-84084Italy Department of Advanced Medical and Surgery Sciences University of Campania“Luigi Vanvitelli”Caserta 81100Italy Eye Center of the 2nd Affiliated Hospital Medical College of Zhejiang UniversityHangzhou 310020China Zhejiang Provincial Key Lab of Ophthalmology Hangzhou 310020China Department of Health and Exercise Science Colorado State UniversityFort Collins CO 80523USA Pacific Parkinson’s Research Centre University of British ColumbiaVancouver BC V6E 2M6Canada Department of Medicine(Neurology)University of British Columbia Vancouver BC V6T 1B7Canada Brain and Mind Center The University of SydneySydney NSW 2006Australia Department of Neurology Ulm UniversityUlm 89081Germany Division of Neurology Department of MedicineQueen Mary HospitalUniversity of Hong KongHong Kong 999077China Department of

Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles have been published on brain *** precise localization of abnormal brain activity,a voxel-level comparison is *** of the large number of voxels in the brain,multiple comparison correction(MCC)must be performed to reduce false positive rates,and a smaller P value(usually including either liberal or stringent MCC)is widely recommended[1].

关键词：帕金森病 precise correction

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Second workshop on theory-informed user modeling for tailoring and personalizing interfaces (humanIZE): Workshop preface

Second workshop on theory-informed user modeling for tailori...

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2018 Joint ACM IUI Workshops, ACMIUI-WS 2018

作者： Graus, Mark Ferwerda, Bruce Tkalcic, Marko Germanakos, Panagiotis Human-Technology Interaction Group Eindhoven University of Technology P.O. Box 513 Eindhoven NL5600 MB Netherlands Department of Computer Science and Informatics School of Engineering Jönköping University P.O. Box 1026 Jönköping SESE-551 11 Sweden Faculty of Computer Science Free University of Bozen-Bolzano Piazza Domenicani 3 Bozen-Bolzano ITI-39100 Italy UX Mobile and Business Services PandI ICD SAP SE Dietmar-Hopp-Allee 16 Walldorf DE69190 Germany Department of Computer Science University of Cyprus P.O. Box 20537 Nicosia1678 Cyprus

The second workshop on Theory-Informed UserModeling for Tailoring and Personalizing Interfaces (humanIZE)1 took place in conjunction with the 23rd annual meeting of the intelligent user interfaces (IUI)2 community in Tokyo, Japan on March 11, 2018. The goal of the workshop was to attract researchers from different fields by accepting contributions on the intersection of practical data mining methods and theoretical knowledge for personalization. A total of eight papers were accepted for this edition of the workshop. © 2018 Copyright for the individual papers remains with the authors.

关键词： User interfaces

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Taste Perception Profiles Are Associated With Adherence to Empirically Derived Dietary Patterns Among Older Adults With Metabolic Syndrome

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Current Developments in Nutrition 2021年 5卷 5140407-5140407页

作者： Gervis, Julie Fernández-Carrión, Rebeca Chui, Kenneth Ma, Jiantao Coltell, Oscar Sorlí, José Barragán, Rocío González, José I. Gimenez-Alba, Ignacio Martinez-Lacruz, Raul Guillem-Saiz, Patricia Pascual-Catelló, Eva Portolés, Olga Corella, Dolores Lichtenstein, Alice Cardiovascular Nutrition Laboratory Jean Mayer USDA Human Nutrition Research Center on Aging Tufts University Department of Preventive Medicine and Public Health School of Medicine University of Valencia Valencia and CIBEROBN Madrid Spain Department of Public Health &amp Community Medicine Tufts University School of Medicine Department of Nutrition Data Science Friedman School of Nutrition Science and Policy Tufts University Department of Computer Languages and Systems Universitat Jaume I Castellón Spain Department of Preventive Medicine and Public Health School of Medicine University of Valencia Valencia Spain

AbstractObjectivesUnderstanding individual-level drivers of food intake is critical when personalizing dietary guidance. One likely driver is taste perception; yet, limited data relate perception of all 5 tastes (sweet, salt, sour, bitter, umami) to dietary patterns (DPs). Our aim was to determine whether a multivariable measure of taste perception, taste perception profiles, was associated with adherence to empirically derived DPs. MethodsParticipants were 367 community-dwelling adults with metabolic syndrome from PREDIMED-Plus, Valencia (55–75 years; 55% female). Six taste perception profiles were derived from 5 taste perception scores via a data-driven clustering approach: Low All (23%), High Bitter (16%), High Umami (17%), Low Bitter & Umami (20%), High All But Bitter (13%) and High All But Umami (11%). DPs were derived via principal component analysis using food groupings tabulated from food frequency questionnaires. Generalized linear models were used to examine relations between taste perception profiles and DP adherence, adjusting for confounders. ResultsThree DPs were identified, explaining 25% of total variance: a high fruit, vegetable and whole grain DP (Fruit/Veg), a high fat, sugar and refined grain DP (Fat/Sug) and a high alcohol, salt and processed meat DP (Alch/Salt). Adherence to the DPs differed by profile. Across all profiles, High Bitter and Low All individuals were most likely to follow the Alch/Salt DP (44% and 39% in highest tertial of adherence, respectively; P = 0.03), while those with High All But Bitter and High Umami tended to follow the Fat/Sug DP (42% and 39% in highest tertial, respectively; P = 0.08). Compared to Low All individuals, after adjusting for age, sex, physical activity, diabetes and BMI, those with Low Bitter & Umami adhered less to the Alch/Salt DP (β [95% CI] = –0.3 [–0.6, –0.03]) while those with High Umami adhered more to the Fat/Sug DP (0.4 [0.1, 0.8]). ConclusionsAmong older adults with metabolic syndrome, taste perc

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Semantics-aware BERT for language understanding

arXiv

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arXiv 2019年

作者： Zhang, Zhuosheng Wu, Yuwei Zhao, Hai Li, Zuchao Zhang, Shuailiang Zhou, Xi Zhou, Xiang Department of Computer Science and Engineering Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China College of Zhiyuan Shanghai Jiao Tong University China CloudWalk Technology Shanghai China

The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machine reading comprehension and natural language inference tasks. However, the existing language representation models including ELMo, GPT and BERT only exploit plain context-sensitive features such as character or word embeddings. They rarely consider incorporating structured semantic information which can provide rich semantics for language representation. To promote natural language understanding, we propose to incorporate explicit contextual semantics from pre-trained semantic role labeling, and introduce an improved language representation model, Semantics-aware BERT (SemBERT), which is capable of explicitly absorbing contextual semantics over a BERT backbone. SemBERT keeps the convenient usability of its BERT precursor in a light fine-tuning way without substantial task-specific modifications. Compared with BERT, semantics-aware BERT is as simple in concept but more powerful. It obtains new state-of-the-art or substantially improves results on ten reading comprehension and language inference tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Semantics

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Harmonized-Multinational qEEG norms (HarMNqEEG)

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NEUROIMAGE 2022年 256卷 119190-119190页

作者： Li, Min Wang, Ying Lopez-Naranjo, Carlos Hu, Shiang Reyes, Ronaldo Cesar Garcia Paz-Linares, Deirel Areces-Gonzalez, Ariosky Hamid, Aini Ismafairus Abd Evans, Alan C. Savostyanov, Alexander N. Calzada-Reyes, Ana Villringer, Arno Tobon-Quintero, Carlos A. Garcia-Agustin, Daysi Yao, Dezhong Dong, Li Aubert-Vazquez, Eduardo Reza, Faruque Razzaq, Fuleah Abdul Omar, Hazim Abdullah, Jafri Malin Galler, Janina R. Ochoa-Gomez, John F. Prichep, Leslie S. Galan-Garcia, Lidice Morales-Chacon, Lilia Valdes-Sosa, Mitchell J. Trondle, Marius Zulkifly, Mohd Faizal Mohd Rahman, Muhammad Riddha Bin Abdul Milakhina, Natalya S. Langer, Nicolas Rudych, Pavel Koenig, Thomas Virues-Alba, Trinidad A. Lei, Xu Bringas-Vega, Maria L. Bosch-Bayard, Jorge F. Valdes-Sosa, Pedro Antonio [a]The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China [b]Cuban Center for Neurocience La Habana Cuba [c]McGill Centre for Integrative Neuroscience Ludmer Centre for Neuroinformatics and Mental Health Montreal Neurological Institute Canada [d]Department of Neurosciences School of Medical Sciences Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [e]Brain and Behaviour Cluster School of Medical Sciences Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [f]Hospital Universiti Sains Malaysia Universiti Sains Malaysia Health Campus Kota Bharu Kelantan 16150 Malaysia [g]Humanitarian Institute Novosibirsk State University Novosibirsk 630090 Russia [h]Laboratory of Psychophysiology of Individual Differences Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine Novosibirsk 630117 Russia [i]Laboratory of Psychological Genetics at the Institute of Cytology and Genetics Siberian Branch of the Russian Academy of Sciences Novosibirsk 630090 Russia [j]University of Pinar del Río “Hermanos Saiz Montes de Oca” Pinar del Río Cuba [k]Department of Neurology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany [l]Department of Cognitive Neurology University Hospital Leipzig Leipzig Germany [m]Center for Stroke Research Charité-Universitätsmedizin Berlin Berlin Germany [n]Grupo Neuropsicología y Conducta - GRUNECO Faculty of Medicine Universidad de Antioquia Colombia [o]Research Department Institución Prestadora de Servicios de Salud IPS Universitaria Colombia [p]The Cuban center aging longevity and health Havana Cuba [q]Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu 2019RU035 China [r]School of Electrical Engineering Zhengzhou University Zhengzhou 4500

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects " and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

关键词： Quantitative EEG EEG cross-spectrum Riemannian geometry Batch effects Z-score Harmonization Malnutrition Covid induced brain dysfunction Developmental Brain Chart

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Artificial Intelligence, Bioinformatics, and Pathology

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Advances in Molecular Pathology 2022年第1期5卷 e1-e24页

作者： Joshua Levy Yunrui Lu Marietta Montivero Ojas Ramwala Jason McFadden Carly Miles Adam Gilbert Diamond Ramya Reddy Ram Reddy Taylor Hudson Zarif Azher Akash Pamal Sameer Gabbita Tess Cronin Abdol Aziz Ould Ismail Tarushii Goel Sanjay Jacob Anish Suvarna Sumanth Ratna Jason Zavras Louis Vaickus Department of Pathology and Laboratory Medicine Emerging Diagnostic and Investigative Technologies Dartmouth Health Lebanon NH USA Department of Dermatology Dartmouth Health Lebanon NH USA Department of Epidemiology Dartmouth College Geisel School of Medicine Hanover NH USA Program in Quantitative Biomedical Sciences Dartmouth College Geisel School of Medicine Hanover NH USA Dartmouth College Geisel School of Medicine Hanover NH USA Department of Biomedical Informatics and Medical Education University of Washington Seattle WA USA Undiagnosed Diseases Program National Human Genome Research Institute Bethesda MD USA Department of Computer Science University of Michigan Ann Arbor MI USA Hanover High School Hanover NH USA Thomas Jefferson High School for Science and Technology Alexandria VA USA Department of Computer Science University of Virginia Charlottesville VA USA University of New Hampshire Durham NH USA White River Junction VA Medical Center White River Junction VT USA Massachusetts Institute of Technology Cambridge MA USA Case Western Reserve University Cleveland OH USA Yale University New Haven CT USA Broad Institute of MIT and Harvard Cambridge MA USA

The advent of complex molecular assays and anatomic imaging platforms has enabled unprecedented characterization of disease pathogenesis. However, challenges remain in formulating diagnostic and prognostic tests that can effectively navigate and synthesize the massive treasure troves of information now available in modern pathology laboratories. Artificial intelligence (AI), and, in particular, machine learning, are pattern mining algorithms that can efficiently uncover biomarkers and risk factors personalized to the individual. These technologies will also have the benefit of providing efficiency gains, resolving ambiguity, and reducing the unnecessary resource expenditures in the Pathology setting. Adoption of AI technologies in these settings can be improved by engaging pathologists on how AI can be meaningfully used in their practice and through dissemination and communication of these core concepts and their potential benefits. In this work, we summarize emerging application areas for AI in the fields of Anatomic and Molecular Pathology.

关键词： Artificial intelligence technologies Artificial neural networks Machine learning algorithms Virtual staining Spatial omics Bioinformatics Image analysis

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Association of BRAF V600E with Hypothalamic-Pituitary-Adrenal Axis Involvement in Erdheim-Chester Disease

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Endocrine and Metabolic science 2020年第1-2期1卷

作者： Hannah-Shmouni, Fady Boyd, Louisa Papadakis, Georgios Z. Tirosh, Amit Gahl, William A Estrada-Veras, Juvianee I. Section on Endocrinology and Genetics Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health Bethesda MD United States Office of the Clinical Director National Human Genome Research Institute National Institutes of Health Bethesda MD United States Department of Medical Imaging Heraklion University Hospital Medical School University of Crete Heraklion 70013 Greece Computational Biomedicine Laboratory (CBML) Institute of Computer Science (ICS) Foundation for Research and Technology Hellas (FORTH) Heraklion 70013 Greece Endocrine Oncology Bioinformatics Lab Department of Endocrinology Sheba Medical Center and Sackler Faculy of Medicine Tel Aviv University Tel Hashomer Israel Section on Human Biochemical Genetics Medical Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda MD United States

Erdheim-Chester disease (ECD) is a rare non-Langerhans cell histiocytosis characterized by uncontrolled inflammation resulting in fibro-inflammatory damage of multiple organs, including the hypothalamic-pituitary-adrenal (HPA) axis. Glucocorticoid insufficiency may occur and is associated with an increased burden of disease and an increased risk of adrenal crisis. Sixty-one ECD subjects (46 males, age 54.3 ± 10.8 years) were evaluated;56.1% (32/57) harbored a somatic activating BRAF V600E variant. Adrenal gland and sellar or suprasellar involvement was present in 18/57 (31.6%) and 9/57 (15.8%) subjects on computed tomography or magnetic resonance imaging, respectively. The BRAF-positive group was more likely to have adrenal gland involvement (56.2% vs. 20.0%;odds ratio (OR) 5.8, 95% confidence interval (CI) 1.5-17.1, P=0.008), with comparable rates for sellar or suprasellar involvement (28.1% vs. 20.0%;OR 1.6, 95% CI 0.5-5.4, P=0.5) and low random morning cortisol values (37.5% vs. 32.0%;OR 1.3, 95% CI 0.4-3.8, P=0.7). High-sensitivity C-reactive protein was significantly higher in the BRAF V600E-positive group with adrenal involvement when compared to the BRAF V600E-negative group without adrenal involvement (mean concentration: 40 mg/dL vs. 5 mg/dL, P=0.046). HPA axis in ECD tends to involve the adrenal glands in BRAF V600E-positive individuals, without influencing the rates of low cortisol levels, although there is a poor biochemical-radiological concordance in ECD. In this cohort, most subjects with HPA axis involvement did not require glucocorticoid or mineralocorticoid therapy. This study systematically demonstrates an association between the somatic activating BRAF V600E variant and the presence of radiographic and biochemical HPA axis involvement in ECD subjects. TRIAL REGISTRATION: *** Identifier: NCT01417520 © 2020

关键词： Adrenal Insufficiency BRAF Erdheim-Chester Disease Inflammation

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