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arXiv 2018年

作者： Varrecchia, Marilena Levine, Joshua Olmo, Gabriella Grangetto, Marco Gai, Marta Di Cunto, Ferdinando Dept. of Control and Computing Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Torino Italy Computer Science Dept. Corso Svizzera 185 Torino Italy Department of Molecular Biotechnology and Health Sciences University of Torino Via Nizza 52 Torino Italy Neuroscience Institute Cavalieri Ottolenghi University of Torino c.o. Azienda Ospedaliero-Universitaria San Luigi Gonzaga Regione Gonzole 10 Orbassano Italy

In this paper we explore detection and tracking of astral microtubules, a sub-population of microtubules which only exists during and immediately before mitosis and aids in the spindle orientation by connecting it to the cell cortex. Its analysis can be useful to determine the presence of certain diseases, such as brain pathologies and cancer. The proposed algorithm focuses on overcoming the problems regarding fluorescence microscopy images and microtubule behaviour by using various image processing techniques and is then compared with three existing algorithms, tested on consistent sets of images. Copyright © 2018, The Authors. All rights reserved.

关键词： Fluorescence microscopy

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Developing a workflow approach for mining online social media data

Developing a workflow approach for mining online social medi...

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2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017

作者： He, Wu Yan, Gongjun Shen, Jiancheng Tian, Xin Dept. of Information Technology and Decision Science Old Dominion University NorfolkVA United States Computer Science Program University of Southern Indiana EvansvilleIN47712 United States Business Leadership and Management Department Regent University Virginia BeachVA23464 United States

ISBN: (纸本)9781538604342

Customers' conversations on social media could shed light into their experience, opinions, feelings, and concerns. To gain valuable knowledge about customers, it becomes increasingly important for businesses to collect, monitor, analyze, summarize, and visualize user-generated data on social media. However, analyzing social media data is challenging due to the vast increase of social media data. In this paper, we present a workflow approach of using established natural language preprocessing, text mining and sentiment analysis techniques to analyze social media data. Then we conducted two experiments to verify the effectiveness of our workflow approach by mining online movie reviews. The results show that our workflow approach is effective in analyzing social media data. © 2017 IEEE.

关键词： Sentiment analysis

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Genetic variant analysis of boys with Autism: A pilot study on linking facial phenotype to genotype

Genetic variant analysis of boys with Autism: A pilot study ...

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2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

作者： Obafemi-Ajayi, Tayo Settles, Luke Su, Yuqing Germeroth, Cynthia Olbricht, Gayla R. Wunsch, Donald C. Takahashi, T. Nicole Miles, Judith Engineering Program Missouri State University Springfield MO United States Mathematics and Statistics Dept. Missouri University of Science and Technology RollaMO United States Information Technology Missouri University of Science and Technology RollaMO United States Electrical and Computer Eng. Dept. Missouri University of Science and Technology RollaMO United States Thompson Center for Autism and Neurodevelopmental Disorders ColumbiaMO United States

ISBN: (纸本)9781509030491

This work examines the validity of facial phenotypes as Autism Spectrum Disorders (ASD) biomarkers in boys with essential autism. A family-based association analysis framework is presented that uses previously identified facially-delineated (FD) clusters to examine relationship between FD clusters and known ASD genes. The hypothesis is that there are certain genetic variants, single nucleotide polymorphisms (SNP), specific to the FD clusters. Although statistical significance was not established, the results identified some candidate SNPs unique to each of the FD clusters that could indicate an underlying etiological difference. Further, recommendations are provided for larger-scale studies that could utilize the analysis framework presented. © 2017 IEEE.

关键词： Biomarkers

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Penetrance of neurodevelopmental copy number variants is associated with variations in cortical morphology

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Biological psychiatry. Cognitive neuroscience and neuroimaging 2025年

作者： Ana I Silva Ida E Sønderby George Kirov Abdel Abdellaoui Ingrid Agartz David Ames Nicola J Armstrong Eric Artiges Tobias Banaschewski Anne S Bassett Carrie E Bearden John Blangero Rune Boen Dorret I Boomsma Robin Bülow Nancy J Butcher Vince Calhoun Linda E Campbell Eva W C Chow Simone Ciufolini Michael C Craig Benedicto Crespo-Farroco Adam C Cunningham Shareefa Dalvie Eileen Daly Paola Dazzan Eco J C de Geus Greig I de Zubicaray Joanne L Doherty Gary Donohoe Mark Drakesmith Thomas Espeseth Vincent Frouin Hugh Garavan David C Glahn Naomi J Goodrich-Hunsaker Penny A Gowland Hans J Grabe Antoine Grigis Maria Gudbrandsen Boris A Gutman Jan Haavik Asta K Håberg Jeremy Hall Andreas Heinz Sarah Hohmann Jouke-Jan Hottenga Sébastien Jacquemont Neda Jahanshad Rachel K Jonas Derek K Jones Erik G Jönsson Sanne Koops Kuldeep Kumar Stephanie Le Hellard Herve Lemaitre Jingyu Liu Astri J Lundervold Jean-Luc Martinot Karen A Mather Donna M McDonald-McGinn Katie L McMahon Allan F McRae Sarah E Medland Clara A Moreau Kieran C Murphy Declan Murphy Robin M Murray Frauke Nees Michael J Owen Marie-Laure Paillère Martinot Diimitri Papadopoulos Orfanos Tomas Paus Luise Poustka Tiago Reis Marques David R Roalf Perminder S Sachdev Freda Scheffler J Eric Schmitt Gunter Schumann Vidar M Steen Dan J Stein Lachlan T Strike Alexander Teumer Anbupalam Thalamuthu Sophia I Thomopoulos Diana Tordesillas-Gutiérrez Julian N Trollor Anne Uhlmann Ariana Vajdi Dennis van 't Ent Therese van Amelsvoort Marianne B M van den Bree Dennis van der Meer Javier Vázquez-Bourgon Julio E Villalón-Reina Uwe Völker Henry Völzke Jacob A S Vorstman Lars T Westlye Nigel Williams Katharina Wittfeld Margaret J Wright Paul M Thompson Ole A Andreassen David E J Linden School for Mental Health and Neuroscience Department of Psychiatry and Neuropsychology Faculty of Health Medicine and Life Sciences Maastricht University Maastricht The Netherlands Neuroscience and Mental Health Innovation Institute Cardiff University Cardiff United Kingdom Center for Magnetic Resonance Research Department of Radiology University of Minnesota Minneapolis MN USA. Electronic address: silvaai@um.edu. Centre for Precision Psychiatry Institute of Clinical Medicine University of Oslo Oslo Norway Department of Medical Genetics Oslo University Hospital Oslo Norway KG Jebsen Centre for Neurodevelopmental Disorders University of Oslo Oslo Norway. Division of Psychological Medicine and Clinical Neurosciences Cardiff University Cardiff United Kingdom Centre for Neuropsychiatric Genetics and Genomics School of Medicine Cardiff University Cardiff United Kingdom. Department of Psychiatry Amsterdam UMC University of Amsterdam Amsterdam the Netherlands. Norwegian Centre for Mental Disorders Research (NORMENT) Institute of Clinical Medicine University of Oslo Oslo Norway Centre for Psychiatry Research Department of Clinical Neuroscience Karolinska Institutet & Stockholm Health Care Services Stockholm Region Stockholm Sweden Department of Psychiatric Research Diakonhjemmet Hospital Oslo Norway. University of Melbourne Academic Unit for Psychiatry of Old Age Kew Victoria Australia. Mathematics and Statistics Curtin University Perth WA Australia. Institut National de la Santé et de la Recherche Médicale INSERM U1299 "Trajectoires développementales et psychiatrie" Université Paris-Saclay Ecole Normale supérieure Paris-Saclay CNRS Centre Borelli Gif-sur-Yvette France Psychiatry Department EPS Barthélémy Durand Etampes Île-de-France France. Department of Child and Adolescent Psychiatry and Psychotherapy Central Institute of Mental Health Medical Faculty Mannheim University of Heidelberg Mannheim Germany. Clinical Genetics Research Program Centre for

BACKGROUND:Copy number variants (CNVs) increase risk for neurodevelopmental conditions. The neurobiological mechanisms linking these high-risk genetic variants to clinical phenotypes are largely unknown. An important question is whether brain abnormalities in individuals carrying CNVs are associated with their degree of penetrance. METHODS:We investigated if increased CNV-penetrance for schizophrenia and other developmental disorders was associated with variations in cortical and subcortical morphology. We pooled T1-weighted brain magnetic resonance imaging and genetic data from 22 cohorts from the ENIGMA-CNV consortium. In the main analyses, we included 9,268 individuals (aged 7 to 90 years, 54% females), from which we identified 398 carriers of 36 neurodevelopmental CNVs at 20 distinct loci. A secondary analysis was performed including additional neuroimaging data from the ENIGMA-22q consortium, including 274 carriers of the 22q11.2 deletion and 291 non-carriers. CNV-penetrance was estimated through penetrance scores that were previously generated from large cohorts of patients and controls. These scores represent the probability risk to develop either schizophrenia or other developmental disorders (including developmental delay, autism spectrum disorder and congenital malformations). RESULTS:For both schizophrenia and developmental disorders, increased penetrance scores were associated with lower surface area in the cerebral cortex and lower intracranial volume. For both conditions, associations between CNV-penetrance scores and cortical surface area were strongest in regions of the occipital lobes, specifically in the cuneus and lingual gyrus. CONCLUSIONS:Our findings link global and regional cortical morphometric features with CNV-penetrance, providing new insights into neurobiological mechanisms of genetic risk for schizophrenia and other developmental disorders.

关键词： autism neuroimaging psychiatric disorders schizophrenia structural imaging

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The effects of the Multicultural Healthy Diet on cognitive decline & Alzheimer's disease risk: A randomized controlled trial in middle-aged adults

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The American journal of clinical nutrition 2025年

作者： Yasmin Mossavar-Rahmani Noorie Hyun Jonathan G Hakun Mindy J Katz Jelena M Pavlovic Henrik Zetterberg Zheng Wang Jasper B Yang Judith Wylie-Rosett James R Hebert Martin J Sliwinski Pamela A Shaw Division of Health Behavior Research & Implementation Science Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Electronic address: yasmin.mossavar-rahmani@einsteinmed.edu. Division of Biostatistics Kaiser Permanente Washington Health Research Institute Seattle WA Department of Biostatistics University of Washington Seattle WA. Department of Neurology The Pennsylvania State University College of Medicine Hershey PA Department of Psychology The Pennsylvania State University University Park PA Department of Public Health Sciences The Pennsylvania State University College of Medicine Hershey PA Center for Healthy Aging The Pennsylvania State University University Park PA. Department of Neurology Albert Einstein College of Medicine Bronx NY. Department of Neurology Albert Einstein College of Medicine & Montefiore Medical Center Bronx NY. Institute of Neuroscience and Physiology Dept. of Psychiatry and Neurochemistry University of Gothenburg Mölndal Sweden Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square London UK UK Dementia Research Institute at UCL London UK Hong Kong Center for Neurodegenerative Diseases InnoHK Hong Kong China Wisconsin Alzheimer's Disease Research Center University of Wisconsin School of Medicine and Public Health University of Wisconsin-Madison Madison WI. Division of Biostatistics Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Division of Biostatistics Kaiser Permanente Washington Health Research Institute Seattle WA. Division of Health Behavior Research & Implementation Science Department of Epidemiology & Population Health Albert Einstein College of Medicine Bronx NY. Department of Epidemiology and Biostatistics and Cancer Prevention and Control Program Arnold School of Public Health University of South Carolina Columbia SC Depart

BACKGROUND:Anti-inflammatory dietary patterns are associated with slower cognitive decline in older adults; however, little is known about effects of an anti-inflammatory dietary pattern in middle-age. OBJECTIVES:To adapt an anti-inflammatory diet to a multicultural setting and assess its impact on cognitive decline and Alzheimer's Disease risk and related dementias in healthy middle-aged adults. METHODS:We performed a phase II pilot randomized clinical trial in adults (40-65 years old; n=290) in Bronx, New York. Participants were assigned to follow either the Multicultural Healthy Diet (MHD) an anti-inflammatory diet, or usual diet (Comparison). Diet was evaluated using National Cancer Institute's Automated Self-Administered 24-hr food records. The primary cognitive outcome was assessed at 9 months following randomization using a global composite score derived from three ambulatory cognitive assessments of visuospatial memory (Grid Memory), processing speed (Symbol Search) and short-term associative memory binding (Color Shapes). Secondary outcomes included performance on individual tests and association of dietary components with cognitive performance. RESULTS:At 9 month follow-up the MHD arm had a lower Dietary Inflammatory Index (DII) score based on self-reported diet, with an adjusted MHD minus Comparison difference of -0.64 (95% CI: -1.02, -0.27) and -0.94 (95% CI: -1.34, -0.54) for the DII and energy-adjusted DII scores respectively, indicating intervention participants had adhered to an anti-inflammatory dietary pattern. Group session and telephone contact completion averaged 93% and 72% respectively for the MHD arm. No statistically significant difference between arms was found in the primary outcome- cognitive global score change- from baseline: -0.06 (95% CI: -0.15, 0.04), p=0.259. CONCLUSIONS:The MHD was feasible and acceptable in this multicultural US cohort. While the influence of MHD at 9 months was non-significant based on the composite cognitive sco

关键词： Alzheimer’s disease and related dementias Diet assessment ambulatory cognitive monitoring cognitive function dietary inflammatory index multicultural healthy diet randomized controlled clinical trial

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Detecting "Smart" Spammers on Social Network: A Topic Model Approach

Detecting "Smart" Spammers on Social Network: A Topic Model ...

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2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Student Research Workshop, SRW 2016

作者： Liu, Linqing Lu, Yao Luo, Ye Zhang, Renxian Itti, Laurent Lu, Jianwei iLab Tongji School of Software Engineering Tongji University China Dept. of Computer Science and Technology Tongji University China Dept. of Computer Science and Neuroscience Program University of Southern California United States Institute of Translational Medicine Tongji University China

ISBN: (纸本)9781941643815

Spammer detection on social network is a challenging problem. The rigid anti-spam rules have resulted in emergence of "smart" spammers. They resemble legitimate users who are difficult to identify. In this paper, we present a novel spammer classification approach based on Latent Dirichlet Allocation (LDA), a topic model. Our approach extracts both the local and the global information of topic distribution patterns, which capture the essence of spamming. Tested on one benchmark dataset and one self-collected dataset, our proposed method outperforms other state-of-the-art methods in terms of averaged F1-score. © 2016 Association for Computational Linguistics.

关键词： Statistics

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Global and risk-group stratified well-being and mental health during the COVID-19 pandemic in adults: Results from the international COH-FIT Study

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Psychiatry Research 2024年 342卷 115972-115972页

作者： Solmi, Marco Thompson, Trevor Estradé, Andrés Agorastos, Agorastos Radua, Joaquim Cortese, Samuele Dragioti, Elena Vancampfort, Davy Thygesen, Lau Caspar Aschauer, Harald Schlögelhofer, Monika Aschauer, Elena Schneeberger, Andres Huber, Christian G. Hasler, Gregor Conus, Philippe Cuénod, Kim Q. Do von Känel, Roland Arrondo, Gonzalo Fusar-Poli, Paolo Gorwood, Philip Llorca, Pierre-Michel Krebs, Marie-Odile Scanferla, Elisabetta Kishimoto, Taishiro Rabbani, Golam Skonieczna-Żydecka, Karolina Brambilla, Paolo Favaro, Angela Takamiya, Akihiro Zoccante, Leonardo Colizzi, Marco Bourgin, Julie Kamiński, Karol Moghadasin, Maryam Seedat, Soraya Matthews, Evan Wells, John Vassilopoulou, Emilia Gadelha, Ary Su, Kuan-Pin Kwon, Jun Soo Kim, Minah Lee, Tae Young Papsuev, Oleg Manková, Denisa Boscutti, Andrea Gerunda, Cristiano Saccon, Diego Righi, Elena Monaco, Francesco Croatto, Giovanni Cereda, Guido Demurtas, Jacopo Brondino, Natascia Veronese, Nicola Enrico, Paolo Politi, Pierluigi Ciappolino, Valentina Pfennig, Andrea Bechdolf, Andreas Meyer-Lindenberg, Andreas Kahl, Kai G. Domschke, Katharina Bauer, Michael Koutsouleris, Nikolaos Winter, Sibylle Borgwardt, Stefan Bitter, Istvan Balazs, Judit Czobor, Pál Unoka, Zsolt Mavridis, Dimitris Tsamakis, Konstantinos Bozikas, Vasilios P. Tunvirachaisakul, Chavit Maes, Michael Rungnirundorn, Teerayuth Supasitthumrong, Thitiporn Haque, Ariful Brunoni, Andre R. Costardi, Carlos Gustavo Schuch, Felipe Barreto Polanczyk, Guilherme Luiz, Jhoanne Merlyn Fonseca, Lais Aparicio, Luana V. Valvassori, Samira S. Nordentoft, Merete Vendsborg, Per Hoffmann, Sofie Have Sehli, Jihed Sartorius, Norman Heuss, Sabina Guinart, Daniel Hamilton, Jane Kane, John Rubio, Jose Sand, Michael Koyanagi, Ai Solanes, Aleix Andreu-Bernabeu, Alvaro Cáceres, Antonia San José Arango, Celso Díaz-Caneja, Covadonga M. Hidalgo-Mazzei, Diego Vieta, Eduard Gonzalez-Peñas, Javier Fortea, Lydia Parellada, Mara Fullana, Miquel A. Verdolini, Norma Andrlíková, Eva Janků, Karolina Millan, Mark J. Honciuc, Mihaela Moniuszko-Mal University of Ottawa Department of Psychiatry ON Canada The Ottawa Hospital Department of Mental Health ON Canada Ottawa Hospital Research Institute (OHRI) Neurosciences Program Ottawa Ontario Canada Early Psychosis: Interventions and Clinical-detection (EPIC) Lab Department of Psychosis Studies Institute of Psychiatry Psychology & Neuroscience King's College London London United Kingdom Centre for Innovation in Mental Health-Developmental Lab School of Psychology University of Southampton and NHS Trust Southampton United Kingdom Charité Universitätsmedizin Berlin Department of Child and Adolescent Psychiatry Berlin Germany Centre for Chronic Illness and Ageing University of Greenwich London United Kingdom University of Southampton Centre for Innovation in Mental Health Southampton United Kingdom Universidad Católica Department of Psychology Montevideo Uruguay Aristotle University of Thessaloniki II. Dept. of Psychiatry Division of Neurosciences Medical School Faculty of Health Sciences Greece Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) Imaging of Mood- and Anxiety-Related Disorders (IMARD) University of Barcelona CIBERSAM Instituto de Salud Carlos III Barcelona Spain Karolinska Institutet Centre for Psychiatric Research and Education Department of Clinical Neuroscience Stockholm Sweden Linköping University Pain and Rehabilitation Centre and Department of Health Medicine and Caring Sciences Linköping Sweden University of Ioannina Research Laboratory Psychology of Patients Families & Health Professionals Department of Nursing School of Health Sciences Ioannina Greece Katholieke Universiteit Leuven (KU Leuven) Department of Rehabilitation Sciences Leuven Belgium National Institute of Public Health University of Southern Denmark Denmark BioPsyC - Biopsychosocial Corporation Non-profit association for Research Funding Ltd. Vienna Austria University of California San Diego California United States University of Basel Universitä

International studies measuring wellbeing/multidimensional mental health before/ during the COVID-19 pandemic, including representative samples for >2 years, identifying risk groups and coping strategies are lacking. COH-FIT is an online, international, anonymous survey measuring changes in well-being (WHO-5) and a composite psychopathology P-score, and their associations with COVID-19 deaths/restrictions, 12 a-priori defined risk individual/cumulative factors, and coping strategies during COVID-19 pandemic (26/04/2020-26/06/2022) in 30 languages (representative, weighted non-representative, adults). T-test, χ², penalized cubic splines, linear regression, correlation analyses were conducted. Analyzing 121,066/142,364 initiated surveys, WHO-5/P-score worsened intra-pandemic by 11.1±21.1/13.2±17.9 points (effect size d=0.50/0.60) (comparable results in representative/weighted non-probability samples). Persons with WHO-5 scores indicative of depression screening (<50, 13% to 32%) and major depression (<29, 3% to 12%) significantly increased. WHO-5 worsened from those with mental disorders, female sex, COVID-19-related loss, low-income country location, physical disorders, healthcare worker occupations, large city location, COVID-19 infection, unemployment, first-generation immigration, to age=18-29 with a cumulative effect. Similar findings emerged for P-score. Changes were significantly but minimally related to COVID-19 deaths, returning to near-pre-pandemic values after >2 years. The most subjectively effective coping strategies were exercise and walking, internet use, social contacts. Identified risk groups, coping strategies and outcome trajectories can inform global public health strategies. © 2024 The Authors

关键词： Covid-19 Mental health P-factor Pandemic Psychiatry Psychopathology Survey Well-being WHO-5

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Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

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arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

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Global Analysis of the Mammalian MHC Class I Immunopeptidome at the Organism-Wide Scale

SSRN

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SSRN 2020年

作者： Kubiniok, Peter Marcu, Ana Bichmann, Leon Kuchenbecker, Leon Schuster, Heiko Hamelin, David Despault, Jérome Kovalchik, Kevin Wessling, Laura Kohlbacher, Oliver Stevanovic, Stefan Rammensee, Hans-Georg Neidert, Marian C. Sirois, Isabelle Caron, Etienne CHU Sainte-Justine Research Center MontrealQCH3T 1C5 Canada Department of Immunology Interfaculty Institute for Cell Biology University of Tübingen TübingenBaden-Württemberg72076 Germany Image-Guided and Functionally Instructed Tumor Therapies University of Tübingen TübingenBaden-Württemberg72076 Germany Applied Bioinformatics Dept. of Computer Science University of Tübingen TübingenBaden-Württemberg72074 Germany Immatics Biotechnologies GmbH Tübingen Baden-Württemberg72076 Germany TübingenBaden-Württemberg72076 Germany Institute for Bioinformatics and Medical Informatics University of Tübingen TübingenBaden-Württemberg72076 Germany Biomolecular Interactions Max Planck Institute for Developmental Biology TübingenBaden-Württemberg72076 Germany University of Tübingen TübingenBaden-WürttembergPLZ Germany Translational Bioinformatics University Hospital Tübingen Tübingen TübingenBaden-Württemberg72076 Germany Clinical Neuroscience Center Department of Neurosurgery University Hospital and University of Zürich Zürich Zürich8057&8091 Switzerland Department of Pathology and Cellular Biology Faculty of Medicine Université de Montréal QCH3T 1J4 Canada

Understanding the molecular principles that govern the composition of the mammalian MHC-I immunopeptidome (MHC-Ii) across different primary tissues is fundamentally important to predict how T cell respond in different contexts in vivo. Here, we performed a global analysis of the mammalian MHC-Ii from 29 and 19 primary human and mouse tissues, respectively. First, we observed that different HLA-A, -B and -C allotypes do not contribute evenly to the global composition of the MHC-Ii across multiple human tissues. Second, w e found that peptides that are presented in a tissue-dependent and -independent manner share very distinct properties. Third, we discovered that proteins that were evolutionarily hyperconserved represent the primary source of the MHC-Ii at the organism-wide scale. Finally, we uncovered a remarkable antigen processing and presentation network that may drive the high level of heterogeneity of the MHC-Ii across different tissues in mammals. This study opens up new avenues toward a system-wide understanding of antigen presentation in vivo and may serve as ground work to understand tissue-dependent T cell responses in autoimmunity, infectious diseases and cancer. © 2020, The Authors. All rights reserved.

关键词： Mammals

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The importance of transparency and reproducibility in artificial intelligence research

arXiv

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arXiv 2020年

作者： Haibe-Kains, Benjamin Adam, George Alexandru Hosny, Ahmed Khodakarami, Farnoosh Waldron, Levi Wang, Bo McIntosh, Chris Kundaje, Anshul Greene, Casey S. Hoffman, Michael M. Leek, Jeffrey T. Huber, Wolfgang Brazma, Alvis Pineau, Joelle Tibshirani, Robert Hastie, Trevor Ioannidis, John P.A. Quackenbush, John Aerts, Hugo J.W.L. Princess Margaret Cancer Centre University Health Network TorontoON Canada Department of Medical Biophysics University of Toronto TorontoON Canada Department of Computer Science University of Toronto TorontoON Canada Ontario Institute for Cancer Research TorontoON Canada Vector Institute for Artificial Intelligence TorontoON Canada Program Brigham and Women's Hospital Harvard Medical School BostonMA United States Radiation Oncology and Radiology Dana-Farber Cancer Institute Brigham and Women's Department of Epidemiology and Biostatistics Institute for Implementation Science in Population Health CUNY Graduate School of Public Health and Health Policy New YorkNY United States Peter Munk Cardiac Centre University Health Network TorontoON Canada Hospital Harvard Medical School BostonMA United States Department of Genetics Stanford University School of Medicine StanfordCA United States Dept. of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Childhood Cancer Data Lab Alex's Lemonade Stand Foundation PhiladelphiaPA United States Department of Biostatistics Johns Hopkins Bloomberg School of Public Health BaltimoreMD United States European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany European Molecular Biology Laboratory European Bioinformatics Institute EMBL-EBI Hinxton United Kingdom McGill University MontrealQC Canada Montreal Institute for Learning Algorithms QC Canada StanfordCA United States Department of Biomedical Data Science Stanford University School of Medicine StanfordCA United States Departments of Medicine of Health Research and Policy and of Biomedical Data Science Stanford University School of Medicine StanfordCA United States Department of Statistics Stanford University School of Humanities and Sciences StanfordCA United States Department of Biostatistics Harvard T.H Chan School of Public Health BostonMA Un

In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening. However, the lack of detailed methods and computer code undermines its scientific value. We identify obstacles hindering transparent and reproducible AI research as faced by McKinney et al and provide solutions with implications for the broader field. Copyright © 2020, The Authors. All rights reserved.

关键词： Artificial intelligence

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