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Multimodal identification of the mouse brain using simultaneous Ca²⁺ imaging and fMRI

Communications Biology 2025年第1期8卷 1-14页

作者： Mandino, Francesca Horien, Corey Shen, Xilin Desrosiers-Grégoire, Gabriel Luo, Wendy Markicevic, Marija Constable, R. Todd Papademetris, Xenophon Chakravarty, Mallar M. Betzel, Richard F. Lake, Evelyn M. R. Department of Radiology and Biomedical Imaging Yale University School of Medicine New Haven CT United States Interdepartmental Neuroscience Program Yale University School of Medicine New Haven CT United States MD/PhD program Yale University School of Medicine New Haven CT United States Computational Brain Anatomy Laboratory Douglas Mental Health University Institute Montreal QC Canada Integrated Program in Neuroscience McGill University Montreal QC Canada Department of Biomedical Engineering Yale University School of Medicine New Haven CT United States Department of Neurosurgery Yale University School of Medicine New Haven CT United States Deparment of Biomedical Informatics and Data Science Yale University New Haven CT United States Department of Psychological and Brain Sciences Indiana University Bloomington IN United States Wu Tsai Institute Yale University New Haven CT United States

Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the prevailing modality in this field—blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI)—suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed. Here, we apply simultaneous wide-field fluorescence calcium imaging and BOLD-fMRI in mice to interrogate individual differences using a connectome-based identification framework adopted from the human fMRI literature. This approach yields high spatiotemporal resolution cell-type specific signals (here, from glia, excitatory, as well as inhibitory interneurons) from the whole cortex. We found mouse multimodal connectome-based identification to be successful and explored various features of these data. © The Author(s) 2025.

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Stratamatch: Prognostic score stratification using a pilot design

arXiv

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arXiv 2020年

作者： Aikens, Rachael C. Rigdon, Joseph Lee, Justin Baiocchi, Michael Goldstone, Andrew B. Chiu, Peter Woo, Y. Joseph Chen, Jonathan H. Interdepartmental Program in Biomedical Informatics Stanford University StanfordCA United States Department of Biostatistics and Data Science Wake Forest School of Medicine Winston-SalemNC United States Quantitative Sciences Unit Stanford University StanfordCA United States Epidemiology and Population Health Stanford University StanfordCA United States Division of Cardiovascular Surgery University of Pennsylvania PhiladelphiaPA United States Department of Cardiothoracic Surgery Stanford University School of Medicine StanfordCA United States Biomedical Informatics Research Institute Stanford University Medical Center StanfordCA United States

Optimal propensity score matching has emerged as one of the most ubiquitous approaches for causal inference studies on observational data;However, outstanding critiques of the statistical properties of propensity score matching have cast doubt on the statistical efficiency of this technique, and the poor scalability of optimal matching to large data sets makes this approach inconvenient if not infeasible for sample sizes that are increasingly commonplace in modern observational data. The stratamatch package provides implementation support and diagnostics for ‘stratified matching designs,’ an approach which addresses both of these issues with optimal propensity score matching for large-sample observational studies. First, stratifying the data enables more computationally efficient matching of large data sets. Second, stratamatch implements a ‘pilot design’ approach in order to stratify by a prognostic score, which may increase the precision of the effect estimate and increase power in sensitivity analyses of unmeasured confounding. Copyright © 2020, The Authors. All rights reserved.

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Implications of self-identified race, ethnicity, and genetic ancestry on genetic association studies in biobanks within health systems

arXiv

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arXiv 2024年

作者： Johnson, Ruth Pasaniuc, Bogdan Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Computer Science University of California Los Angeles Los AngelesCA90095 United States Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA90095 United States Department of Pathology Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA90095 United States Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los AngelesCA90095 United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA90095 United States Institute of Precision Health University of California Los Angeles Los AngelesCA90095 United States

Precision medicine aims to create biomedical solutions tailored to specific factors that affect disease risk and treatment responses within the population. The success of the genomics era and recent widespread availability of electronic health records (EHR) has ushered in a new wave of genomic biobanks connected to EHR databases (EHR-linked biobanks). This perspective aims to discuss how race, ethnicity, and genetic ancestry are currently utilized to study common disease variation through genetic association studies. Although genetic ancestry plays a significant role in shaping the genetic landscape underlying disease risk in humans, the overall risk of a disease is caused by a complex combination of environmental, sociocultural, and genetic factors. When using EHR-linked biobanks to interrogate underlying disease etiology, it is also important to be aware of how the biases associated with commonly used descent-associated concepts such as race and ethnicity can propagate to downstream analyses. We intend for this resource to support researchers who perform or analyze genetic association studies in the EHR-linked biobank setting such as those involved in consortium-wide biobanking efforts. We provide background on how race, ethnicity, and genetic ancestry play a role in current association studies, highlight considerations where there is no consensus about best practices, and provide transparency about the current shortcomings. © 2024, CC BY.

关键词： Genome

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Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Research Square

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Research Square 2021年

作者： Zhang, Martin Jinye Hou, Kangcheng Pasaniuc, Bogdan Price, Alkes L. Dey, Kushal K. Jagadeesh, Karthik A. Weinand, Kathryn Sakaue, Saori Taychameekiatchai, Aris Rao, Poorvi Pisco, Angela Oliveira Zou, James Wang, Bruce Gandal, Michael Raychaudhuri, Soumya Harvard University United States Osaka University Japan Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Center for Data Sciences Brigham and Women’s Hospital BostonMA United States Division of Genetics Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Rheumatology Inflammation and Immunity Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Medicine and Liver Center University of California San Francisco San FranciscoCA United States Developmental and Stem Cell Biology Graduate Program University of California San Francisco San FranciscoCA United States Chan Zuckerberg Biohub San FranciscoCA United States Department of Electrical Engineering Stanford University Palo AltoCA United States Department of Biomedical Data Science Stanford University Palo AltoCA United States Department of Psychiatry David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Program in Neurobehavioral Genetics Semel Institute David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Versus Arthritis Centre for Genetics and Genomic

Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution;scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N =341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states;subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region;and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes. © 2021, CC BY.

关键词： RNA

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Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

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Scientific data 2021年第1期8卷 242页

作者： Julien Cohen-Adad Eva Alonso-Ortiz Mihael Abramovic Carina Arneitz Nicole Atcheson Laura Barlow Robert L Barry Markus Barth Marco Battiston Christian Büchel Matthew Budde Virginie Callot Anna J E Combes Benjamin De Leener Maxime Descoteaux Paulo Loureiro de Sousa Marek Dostál Julien Doyon Adam Dvorak Falk Eippert Karla R Epperson Kevin S Epperson Patrick Freund Jürgen Finsterbusch Alexandru Foias Michela Fratini Issei Fukunaga Claudia A M Gandini Wheeler-Kingshott Giancarlo Germani Guillaume Gilbert Federico Giove Charley Gros Francesco Grussu Akifumi Hagiwara Pierre-Gilles Henry Tomáš Horák Masaaki Hori James Joers Kouhei Kamiya Haleh Karbasforoushan Miloš Keřkovský Ali Khatibi Joo-Won Kim Nawal Kinany Hagen H Kitzler Shannon Kolind Yazhuo Kong Petr Kudlička Paul Kuntke Nyoman D Kurniawan Slawomir Kusmia René Labounek Maria Marcella Laganà Cornelia Laule Christine S Law Christophe Lenglet Tobias Leutritz Yaou Liu Sara Llufriu Sean Mackey Eloy Martinez-Heras Loan Mattera Igor Nestrasil Kristin P O'Grady Nico Papinutto Daniel Papp Deborah Pareto Todd B Parrish Anna Pichiecchio Ferran Prados Àlex Rovira Marc J Ruitenberg Rebecca S Samson Giovanni Savini Maryam Seif Alan C Seifert Alex K Smith Seth A Smith Zachary A Smith Elisabeth Solana Y Suzuki George Tackley Alexandra Tinnermann Jan Valošek Dimitri Van De Ville Marios C Yiannakas Kenneth A Weber Ii Nikolaus Weiskopf Richard G Wise Patrik O Wyss Junqian Xu NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. jcohen@polymtl.ca. Functional Neuroimaging Unit CRIUGM Université de Montréal Montreal QC Canada. jcohen@polymtl.ca. Mila - Quebec AI Institute Montreal QC Canada. jcohen@polymtl.ca. NeuroPoly Lab Institute of Biomedical Engineering Polytechnique Montreal Montreal QC Canada. Department of Radiology Swiss Paraplegic Centre Nottwil Switzerland. Centre for Advanced Imaging The University of Queensland Brisbane Australia. Department of Radiology University of British Columbia Vancouver BC Canada. Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Department of Radiology Harvard Medical School Boston MA USA. Harvard-Massachusetts Institute of Technology Health Sciences & Technology Cambridge MA USA. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia. NMR Research Unit Queen Square MS Centre UCL Queen Square Institute of Neurology Faculty of Brain Sciences University College London London UK. Department of Systems Neuroscience University Medical Center Hamburg-Eppendorf Hamburg Germany. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Aix-Marseille Univ CNRS CRMBM Marseille France. APHM Hopital Universitaire Timone CEMEREM Marseille France. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville TN USA. Department of Computer and Software Engineering Polytechnique Montreal Montreal Canada. CHU Sainte-Justine Research Centre Montreal QC Canada. Centre de Recherche CHUS CIMS Sherbrooke Canada. Sherbrooke Connectivity Imaging Lab (SCIL) Computer Science department Université de Sherbrooke Sherbrooke Canada. Université de Strasbourg CNRS ICube Strasbourg France. UHB - University Hospital Brno and Masaryk University Department of Radiology and Nuclear

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Author Correction: Universal DNA methylation age across mammalian tissues

Nature aging

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Nature aging 2023年第11期3卷 1462页

作者： A T Lu Z Fei A Haghani T R Robeck J A Zoller C Z Li R Lowe Q Yan J Zhang H Vu J Ablaeva V A Acosta-Rodriguez D M Adams J Almunia A Aloysius R Ardehali A Arneson C S Baker G Banks K Belov N C Bennett P Black D T Blumstein E K Bors C E Breeze R T Brooke J L Brown G G Carter A Caulton J M Cavin L Chakrabarti I Chatzistamou H Chen K Cheng P Chiavellini O W Choi S M Clarke L N Cooper M L Cossette J Day J DeYoung S DiRocco C Dold E E Ehmke C K Emmons S Emmrich E Erbay C Erlacher-Reid C G Faulkes S H Ferguson C J Finno J E Flower J M Gaillard E Garde L Gerber V N Gladyshev V Gorbunova R G Goya M J Grant C B Green E N Hales M B Hanson D W Hart M Haulena K Herrick A N Hogan C J Hogg T A Hore T Huang J C Izpisua Belmonte A J Jasinska G Jones E Jourdain O Kashpur H Katcher E Katsumata V Kaza H Kiaris M S Kobor P Kordowitzki W R Koski M Krützen S B Kwon B Larison S G Lee M Lehmann J F Lemaitre A J Levine C Li X Li A R Lim D T S Lin D M Lindemann T J Little N Macoretta D Maddox C O Matkin J A Mattison M McClure J Mergl J J Meudt G A Montano K Mozhui J Munshi-South A Naderi M Nagy P Narayan P W Nathanielsz N B Nguyen C Niehrs J K O'Brien P O'Tierney Ginn D T Odom A G Ophir S Osborn E A Ostrander K M Parsons K C Paul M Pellegrini K J Peters A B Pedersen J L Petersen D W Pietersen G M Pinho J Plassais J R Poganik N A Prado P Reddy B Rey B R Ritz J Robbins M Rodriguez J Russell E Rydkina L L Sailer A B Salmon A Sanghavi K M Schachtschneider D Schmitt T Schmitt L Schomacher L B Schook K E Sears A W Seifert A Seluanov A B A Shafer D Shanmuganayagam A V Shindyapina M Simmons K Singh I Sinha J Slone R G Snell E Soltanmaohammadi M L Spangler M C Spriggs L Staggs N Stedman K J Steinman D T Stewart V J Sugrue B Szladovits J S Takahashi M Takasugi E C Teeling M J Thompson B Van Bonn S C Vernes D Villar H V Vinters M C Wallingford N Wang R K Wayne G S Wilkinson C K Williams R W Williams X W Yang M Yao B G Young B Zhang Z Zhang P Zhao Y Zhao W Zhou J Zimmermann J Ernst K Raj S Horvath Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA. Altos Labs San Diego Institute of Science San Diego CA USA. Department of Biostatistics Fielding School of Public Health University of California Los Angeles Los Angeles CA USA. Department of Statistics University of California Riverside Riverside CA USA. Zoological SeaWorld Parks and Entertainment Orlando FL USA. Altos Labs Cambridge Institute of Science Cambridge UK. Bioinformatics Interdepartmental Program University of California Los Angeles CA USA. Department of Biological Chemistry University of California Los Angeles Los Angeles CA USA. Department of Biology University of Rochester Rochester NY USA. Department of Neuroscience Peter O'Donnell Jr. Brain Institute University of Texas Southwestern Medical Center Dallas TX USA. Department of Biology University of Maryland College Park MD USA. Loro Parque Fundacion Puerto de la Cruz Spain. Department of Biology University of Kentucky Lexington KY USA. Division of Cardiology Department of Internal Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA. Marine Mammal Institute Oregon State University Newport OR USA. School of Science and Technology Clifton Campus Nottingham Trent University Nottingham UK. School of Life and Environmental Sciences the University of Sydney Sydney New South Wales Australia. Department of Zoology and Entomology University of Pretoria Hatfield South Africa. Busch Gardens Tampa Tampa FL USA. Department of Ecology and Evolutionary Biology University of California Los Angeles Los Angeles CA USA. Rocky Mountain Biological Laboratory Crested Butte CO USA. Altius Institute for Biomedical Sciences Seattle WA USA. Epigenetic Clock Development Foundation Los Angeles CA USA. Center for Species Survival Smithsonian Conservation Biology Institute Front Royal VA USA. Department of Evolution Eco

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ESICM LIVES 2016: part two

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Intensive Care Medicine Experimental 2016年第1期4卷 205-404页

作者： S. Sivakumar F. S. Taccone K. A. Desai C. Lazaridis M. Skarzynski M. Sekhon W. Henderson D. Griesdale L. Chapple A. Deane L. Williams R. Strickland K. Lange D. Heyland M. Chapman M. J. Rowland P. Garry J. Westbrook R. Corkill C. A. Antoniades K. T. Pattinson G. Fatania A. J. Strong R. B. Myers C. M. Jermaine C. S. Robertson C. G. Rusin J. Hofmeijer L. Sondag M. C. Tjepkema-Cloostermans A. Beishuizen F. H. Bosch M. J. A. M. van Putten L. Carteron C. Patet D. Solari M. Oddo M. A. Ali C. Dias R. Almeida A. Vaz-Ferreira J. Silva E. Monteiro A. Cerejo A. P. Rocha A. A. Elsayed A. M. Abougabal B. N. Beshey K. M. Alzahaby S. Pozzebon A. Blandino Ortiz S. Cristallini O. Lheureux A. Brasseur J. L. Vincent J. Creteur M. Hravnak K. Yousef Y. Chang E. Crago R. M. Friedlander S. A. Abdelmonem S. A. Tahon T. A. Helmy H. S. Meligy F. Puig I. Dunn-Siegrist J. Pugin S. Gupta D. Govil S. Srinivasan S. J. Patel J. K. N A. Gupta D. S. Tomar M. Shafi R. Harne D. P. Arora N. Talwar S. Mazumdar E. E. Papakrivou D. Makris E. Manoulakas B. Tsolaki B. Karadodas E. Zakynthinos I. Palacios Garcia A. Diaz Martin V. Sanchez Encinares M. Pachón Ibañez J. Garnacho Montero G. Labrador T. Cebrero Cangueiro V. Poulose J. Koh J. W. Kam H. Yeter A. Kara O. Aktepe A. Topeli I. Tsolakoglou G. Intas P. Stergiannis A. A. Kolaros E. Chalari E. Athanasiadou A. Martika G. Fildisis V. Faivre C. Mengelle B. Favier D. Payen A. Poppe M. S. Winkler E. Mudersbach J. Schreiber M. L. Wruck E. Schwedhelm S. Kluge C. Zöllner T. Tavladaki A. M. Spanaki H. Dimitriou E. Kondili C. Choulaki E. Meleti D. Kafetzopoulos D. Georgopoulos G. Briassoulis A. García-de la Torre M. V. de la Torre-Prados T. Tsvetanova-Spasova P. Nuevo-Ortega C. Rueda-Molina A. Fernández-Porcel E. Camara-Sola L. Salido-Díaz A. García-Alcántara D. E. Meleti B. Suberviola J. Riera L. Rellan M. Sanchez J. C. Robles E. Lopez R. Vicente E. Miñambres M. Santibañez M. Le Guen J. Moore N. Mason M. Windpassinger O. Plattner E. Mascha D. I. Sessler Outcomes Research U. Melia J. Fontanet J. P. van den Berg M. Baylor College of Medicine Neurology/Neurocritical Care Houston USA Erasmus Hospital Intensive Care Medicine Brussels Belgium Centre Hospitalier Régional Orléans Réaimation Médicale Orléans France University of British Columbia Vancouver Canada University of Adelaide Discipline of Acute Care Medicine Adelaide Australia Royal Adelaide Hospital Intensive Care Adelaide Australia Griffith University Menzies Health Institute of Queensland Gold Coast Australia University of Adelaide Discipline of Medicine Adelaide Australia Kingston General Hospital Clinical Evaluation Research Unit Kingston Canada University of Oxford Nuffield Department of Clinical Neurosciences Oxford UK Oxford University Hospitals NHS Foundation Trust Neurosciences Intensive Care Unit Oxford UK King’s College Hospital Department of Neurosurgery London UK King’ College London Institute of Psychiatry Psychology and Neuroscience Department of Clinical Neuroscience London UK Rice University Computer Science Houston USA Baylor College of Medicine Neurosurgery Houston USA Baylor College of Medicine Pediatric Cardiology Houston USA University of Twente Clinical Neurophysiology Enschede Netherlands Rijnstate Hospital Neurology Arnhem Netherlands Medical Spectrum Twente Clinical Neurophysiology Enschede Netherlands Medical Spectrum Twente Intensive Care Enschede Netherlands Rijnstate Hospital Intensive Care Arnhem Netherlands CHUV Department of Intensive Care Medicine Neuroscience Critical Care Research Group Lausanne Switzerland Aga Khan University Hospital Anaesthesiology Karachi Pakistan Centro Hospitalar São João Intensive Care Porto Portugal Faculty of Medicine University of Porto Medicine Porto Portugal Faculdade de Ciências Universidade do Porto Departamento de Matemática Porto Portugal Centro de Matemática Universidade do Porto Porto Portugal The Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine Zaragoza Spain Centro Hospitalar

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ESICM LIVES 2016: part three

引用

Intensive Care Medicine Experimental 2016年第1期4卷 405-607页

作者： Velasquez, T. Mackey, G. Lusk, J. Kyle, U. G. Fontenot, T. Marshall, P. Shekerdemian, L. S. Coss-Bu, J. A. Nishigaki, A. Yatabe, T. Tamura, T. Yamashita, K. Yokoyama, M. Ruiz-Rodriguez, J. C. Encina, B. Belmonte, R. Troncoso, I. Tormos, P. Riveiro, M. Baena, J. Sanchez, A. Bañeras, J. Cordón, J. Duran, N. Ruiz, A. Caballero, J. Nuvials, X. Riera, J. Serra, J. Rutten, A. M. F. van Ieperen, S. N. M. Der Kinderen, E. P. H. M. Van Logten, T. Kovacikova, L. Skrak, P. Zahorec, M. Akcan-Arikan, A. Silva, J. C. Goldsworthy, M. Wood, D. Harrison, D. Parslow, R. Davis, P. Pappachan, J. Goodwin, S. Ramnarayan, P. Chernyshuk, S. Yemets, H. Zhovnir, V. Pulitano’, S. M. De Rosa, S. Mancino, A. Villa, G. Tosi, F. Franchi, P. Conti, G. Patel, B. Khine, H. Shah, A. Sung, D. Singer, L. Haghbin, S. Inaloo, S. Serati, Z. Idei, M. Nomura, T. Yamamoto, N. Sakai, Y. Yoshida, T. Matsuda, Y. Yamaguchi, Y. Takaki, S. Yamaguchi, O. Goto, T. Longani, N. Medar, S. Abdel-Aal, I. R. El Adawy, A. S. Mohammed, H. M. E. H. Mohamed, A. N. Parry, S. M. Knight, L. D. Denehy, L. De Morton, N. Baldwin, C. E. Sani, D. Kayambu, G. da Silva, V. Z. M. Phongpagdi, P. Puthucheary, Z. A. Granger, C. L. Rydingsward, J. E. Horkan, C. M. Christopher, K. B. McWilliams, D. Jones, C. Reeves, E. Atkins, G. Snelson, C. Aitken, L. M. Rattray, J. Kenardy, J. Hull, A. M. Ullman, A. Le Brocque, R. Mitchell, M. Davis, C. Macfarlane, B. Azevedo, J. C. Rocha, L. L. De Freitas, F. F. M. Cavalheiro, A. M. Lucinio, N. M. Lobato, M. S. Ebeling, G. Kraegpoeth, A. Laerkner, E. De Brito-Ashurst, I. White, C. Gregory, S. Forni, L. G. Flowers, E. Curtis, A. Wood, C. A. Siu, K. Venkatesan, K. Muhammad, J. B. H. Ng, L. Seet, E. Baptista, N. Escoval, A. Tomas, E. Agrawal, R. Mathew, R. Varma, A. Dima, E. Charitidou, E. Perivolioti, E. Pratikaki, M. Vrettou, C. Giannopoulos, A. Zakynthinos, S. Routsi, C. Atchade, E. Houzé, S. Jean-Baptiste, S. Thabut, G. Genève, C. Tanaka, S. Lortat-Jacob, B. Augustin, P. Desmard, M. Montravers, P. de Molina, F. J. González Barbadillo, S. Alejandro, R. Texas Children’s Hospital Clinical Nutriiton Houston USA Texas Children’s Hospital Intensive Care Houston USA Baylor College of Medicine Pediatrics Houston USA Kochi Medical School Department of Anesthesiology and Intensive Care Medicine Nankoku Japan Vall d’ Hebron University Hospital Critical Care Department Barcelona Spain Vall d’ Hebron University Hospital Anesthesia & Reanimation Department Barcelona Spain Vall d’ Hebron University Hospital Neurocritical Care Department Barcelona Spain Vall d’ Hebron University Hospital Coronary Care Unit Barcelona Spain Sagrat Cor University Hospital Critical Care Department Barcelona Spain St Elisabeth Twee Steden Hospital ICU Tilburg Netherlands National Institute of Cardiovascular Diseases PCICU Bratislava Slovakia National Institute of Cardiovascular Diseases Bratislava Slovakia National Institute of Cardiovascular Diseases Pediatric Cardiac Intensive Care Unit Bratislava Slovakia Texas Children’s Hospital Renal Service Houston USA Bristol Royal Hospital for Children Paediatric Intensive Care Unit Bristol UK Intensive Care National Audit & Research Centre (ICNARC) London UK University of Leeds Leeds UK Southampton University Hospitals NHS Trust Southampton UK Great Ormond Street Hospital London UK UCCC ICU Kyiv Ukraine Catholic University Department of Anesthesia and Intensive Care Rome Italy International Renal Research Institute of Vicenza (IRRIV) Department of Nephrology Dialysis and Transplantation Vicenza Italy University of Florence Department of Health Science Section of Anaesthesiology and Intensive Care Florence Italy The Children’s Hospital at Montefiore Pediatric Critical Care Bronx USA The Children’s Hospital at Montefiore Bronx USA Shiraz University of Medical Sciences Pediatric intensive Care Shiraz Islamic Republic of Iran Shiraz University of Medical Sciences Shiraz Islamic Republic of Iran Yokohama City University Hospital Intensive Care Unit Yokohama Japan Yokohama City Univ

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