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Unlocking capacities of viral genomics for the COVID-19 pandemic response

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arXiv 2021年

作者： Knyazev, Sergey Chhugani, Karishma Sarwal, Varuni Ayyala, Ram Singh, Harman Karthikeyan, Smruthi Deshpande, Dhrithi Comarova, Zoia Lu, Angela Porozov, Yuri Wu, Aiping Abedalthagafi, Malak S. Nagaraj, Shivashankar H. Smith, Adam L. Skums, Pavel Ladner, Jason Lam, Tommy Tsan-Yuk Wu, Nicholas C. Zelikovsky, Alex Knight, Rob Crandall, Keith A. Mangul, Serghei Department of Computer Science College of Art and Science Georgia State University 1 Park Place AtlantaGA30303 United States Department of Pharmacology and Pharmaceutical Sciences School of Pharmacy University of Southern California 1985 Zonal Avenue Los AngelesCA90089 United States Department of Computer Science University of California Los Angeles 580 Portola Plaza Los AngelesCA90095 United States Department of Neuroscience College of Life Sciences University of California Los Angeles 580 Portola Plaza Los AngelesCA90095 United States Department of Electrical Engineering Indian Institute of Technology Hauz Khas New Delhi110016 India Department of Pediatrics University of California San Diego San DiegoCA United States Paradigm Environmental 3911 Old Lee Highway FairfaxVA22030 United States Department of Pharmacology and Pharmaceutical Sciences School of Pharmacy University of Southern California 1985 Zonal Avenue Los AngelesCA90089-9121 United States World-Class Research Center Digital Biodesign and Personalized Healthcare I.M. Sechenov First Moscow State Medical University Moscow Russia Department of Computational Biology Sirius University of Science and Technology Sochi Russia Center for Systems Medicine Institute of Basic Medical Sciences Chinese Academy of Medical Sciences Peking Union Medical College Beijing100005 China Suzhou Institute of Systems Medicine Suzhou215123 China Genomics Research Department Saudi Human Genome Project King Fahad Medical City King Abdulaziz City for Science and Technology Riyadh Saudi Arabia Centre for Genomics and Personalised Health Queensland University of Technology BrisbaneQLD4059 Australia Translational Research Institute Brisbane Australia Astani Department of Civil and Environmental Engineering University of Southern California 3620 South Vermont Avenue Los AngelesCA90089 United States Department of Computer Science College of Art and Science Georgia State University 1 Park Place Atlanta

More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19. © 2021, CC BY-NC-ND.

关键词： SARS

Salience-Default Mode Functional Network Connectivity Linked to Positive and Negative Symptoms of Schizophrenia (vol 45, pg 892, 2018)

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SCHIZOPHRENIA BULLETIN 2019年第6期45卷 1382-1382页

作者： Hare, Stephanie M. Neuroscience Institute Georgia State University Atlanta GA To whom correspondence should be addressed Neuroscience Institute Georgia State University PO Box 5030 Atlanta GA 30302-5030 USA tel: 262-364-7427 fax: 404-413-5446 e-mail: share1@student.gsu.edu Psychiatry Service San Francisco VA Medical Center San Francisco CA Department of Psychiatry University of California San Francisco CA Psychiatry Service San Francisco VA Medical Center San Francisco CA Department of Psychiatry University of California San Francisco CA The Mind Research Network Albuquerque NM Department of Psychiatry and Behavioral Sciences The University of New Mexico Albuquerque NM Department of Psychiatry University of North Carolina at Chapel Hill Chapel Hill NC Division of Computer Science and Engineering CAIIT Chonbuk National University Jeonju Republic of Korea Department of Psychiatry University of Minnesota Minneapolis MN Department of Psychiatry University of Minnesota Minneapolis MN Geriatric Research Education and Clinical Center (GRECC) Minneapolis VA Health Care System Minneapolis MN Department of Psychiatry School of Medicine University of California San Diego San Diego CA Department of Psychiatry and Human Behavior University of California Irvine Irvine CA Department of Psychiatry and Human Behavior University of California Irvine Irvine CA Department of Psychiatry and Human Behavior University of California Irvine Irvine CA The Mind Research Network Albuquerque NM Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM Neuroscience Institute Georgia State University Atlanta GA The Mind Research Network Albuquerque NM Department of Psychology Georgia State University Atlanta GA

Schizophrenia is a complex, debilitating mental disorder characterized by wide-ranging symptoms including delusions, hallucinations (so-called positive symptoms), and impaired motor and speech/language production (so-called negative symptoms). Salience-monitoring theorists propose that abnormal functional communication between the salience network (SN) and default mode network (DMN) begets positive and negative symptoms of schizophrenia, yet prior studies have predominately reported links between disrupted SN/DMN functional communication and positive symptoms. It remains unclear whether disrupted SN/DMN functional communication explains (1) solely positive symptoms or (2) both positive and negative symptoms of schizophrenia. To address this question, we incorporate time-lag-shifted functional network connectivity (FNC) analyses that explored coherence of the resting-state functional magnetic resonance imaging signal of 3 networks (anterior DMN, posterior DMN, and SN) with fixed time lags introduced between network time series (1 TR = 2 s; 2 TR = 4 s). Multivariate linear regression analysis revealed that severity of disordered thought and attentional deficits were negatively associated with 2 TR-shifted FNC between anterior DMN and posterior DMN. Meanwhile, severity of flat affect and bizarre behavior were positively associated with 1 TR-shifted FNC between anterior DMN and SN. These results provide support favoring the hypothesis that lagged SN/DMN functional communication is associated with both positive and negative symptoms of schizophrenia.

关键词： ICA salience network default mode network positive symptoms negative symptoms resting-state fMRI

The users' perspective on the privacy-utility trade-offs in health recommender systemsi

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arXiv 2018年

作者： Valdez, Andre Calero Ziee, Martina Chair of Communication Science Human-Computer Interaction Center RWTH Aachen University Germany Campus Boulevard 57 Aachen52074 Germany

Privacy is a major good for users of personalized services such as recommender systems. When applied to the field of health informatics, privacy concerns of users may be amplified, but the possible utility of such services is also high. Despite availability of technologies such as k-anonymity, differential privacy, privacy-aware recommendation, and personalized privacy trade-offs, little research has been conducted on the users' willingness to share health data for usage in such systems. In two conjoint-decision studies (sample size n = 521), we investigate importance and utility of privacy-preserving techniques related to sharing of personal health data for k-anonymity and differential privacy. Users were asked to pick a preferred sharing scenario depending on the recipient of the data, the benefit of sharing data, the type of data, and the parameterized privacy. Users disagreed with sharing data for commercial purposes regarding mental illnesses and with high de-anonymization risks but showed little concern when data is used for scientific purposes and is related to physical illnesses. Suggestions for health recommender system development are derived from the findings. Copyright © 2018, The Authors. All rights reserved.

关键词： Recommender systems

An open science study of ageing in companion dogs (vol 602, g 51, 2022)

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NATURE 2022年第7924期608卷 E33-E33页

作者： Creevy, Kate E. Akey, Joshua M. Kaeberlein, Matt Promislow, Daniel E. L. Department of Small Animal Clinical Sciences Texas A&M University College of Veterinary Medicine & Biomedical Sciences College Station TX USA Lewis-Sigler Institute for Integrative Genomics Princeton University Princeton NJ USA Department of Laboratory Medicine and Pathology University of Washington School of Medicine Seattle WA USA Department of Biology University of Washington Seattle WA USA Institute for Stem Cell and Regenerative Medicine University of Washington Seattle WA USA Department of Clinical Microbiology and Immunology Sackler Faculty of Medicine Tel Aviv University Tel Aviv Israel Blavatnik School of Computer Science Tel Aviv University Tel Aviv Israel Santa Fe Institute Santa Fe NM USA Cornell Veterinary Biobank College of Veterinary Medicine Cornell University Ithaca NY USA Department of Sociology University of Washington Seattle WA USA Center for Studies in Demography and Ecology Seattle WA USA Department of Small Animal Medicine and Surgery University of Georgia College of Veterinary Medicine Athens GA USA Department of Veterinary Physiology and Pharmacology Texas A&M University College of Veterinary Medicine & Biomedical Sciences College Station TX USA Department of Family Medicine University of Washington Seattle WA USA Department of Epidemiology University of Washington Seattle WA USA Department of Global Health University of Washington Seattle WA USA Epidemiology Program Fred Hutchinson Cancer Research Center Seattle WA USA Department of Veterinary Pathobiology Texas A&M University College of Veterinary Medicine & Biomedical Sciences College Station TX USA Bioinformatics and Integrative Biology University of Massachusetts Chan Medical School Worcester MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Biostatistics University of Washington Seattle WA USA Division of Public Health Sciences Fred Hutchinson Cancer Research Center Seattle WA USA Department of Population Health Sciences Vir

Considerations and Recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 — In vivo small-animal imaging

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arXiv 2022年

作者： Jelescu, Ileana O. Grussu, Francesco Ianus, Andrada Hansen, Brian Barrett, Rachel L.C. Aggarwal, Manisha Michielse, Stijn Nasrallah, Fatima Syeda, Warda Wang, Nian Veraart, Jelle Roebroeck, Alard Bagdasarian, Andrew F. Eichner, Cornelius Sepehrband, Farshid Zimmermann, Jan Soustelle, Lucas Bowman, Christien Tendler, Benjamin C. Hertanu, Andreea Jeurissen, Ben Verhoye, Marleen Frydman, Lucio de Looij, Yohan van Hike, David Dunn, Jeff F. Miller, Karla Landman, Bennett A. Shemesh, Noam Anderson, Adam McKinnon, Emilie Farquharson, Shawna Acqua, Flavio Dell Pierpaoli, Carlo Drobnjak, Ivana Leemans, Alexander Harkins, Kevin D. Descoteaux, Maxime Xu, Duan Huang, Hao Santin, Mathieu D. Grant, Samuel C. Obenaus, Andre Kim, Gene S. Wu, Dan Le Bihan, Denis Blackband, Stephen J. Ciobanu, Luisa Fieremans, Els Bai, Ruiliang Leergaard, Trygve B. Zhang, Jiangyang Dyrby, Tim B. Johnson, G. Allan Cohen-Adad, Julien Budde, Matthew D. Schilling, Kurt G. Department of Radiology Lausanne University Hospital University of Lausanne Lausanne Switzerland CIBM Center for Biomedical Imaging Ecole Polytechnique Fédérale de Lausanne Lausanne Switzerland Radiomics Group Vall d’Hebron Institute of Oncology Vall d’Hebron Barcelona Hospital Campus Barcelona Spain Queen Square MS Centre Queen Square Institute of Neurology Faculty of Brain Sciences University College London London United Kingdom Champalimaud Research Champalimaud Foundation Lisbon Portugal Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Department of Neuroimaging Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom NatBrainLab Department of Forensics and Neurodevelopmental Sciences Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States Maastricht University Medical Center Maastricht Netherlands The Queensland Brain Institute The University of Queensland Queensland Australia Melbourne Neuropsychiatry Centre The University of Melbourne ParkvilleVIC Australia Department of Radiology and Imaging Sciences Indiana University IN United States Stark Neurosciences Research Institute Indiana University School of Medicine IN United States Center for Biomedical Imaging NYU Grossman School of Medicine New YorkNY United States Faculty of psychology and Neuroscience Maastricht University Maastricht Netherlands Department of Chemical & Biomedical Engineering FAMU-FSU College of Engineering Florida State University TallahasseeFL United States Center for Interdisciplinary Magnetic Resonance National HIgh Magnetic Field Laboratory TallahasseeFL United States Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany USC Stevens Neuroimaging and Informatics Instit

Small-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected recommendations and guidelines from the diffusion community, on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We then give guidelines for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including pre-processing, model-fitting, and tractography. Finally, we provide an online resource which lists publicly available preclinical dMRI datasets and software packages, to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. While we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal herein is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge. © 2022, CC BY-NC-ND.

关键词： Invertebrates

Comparative and demographic analysis of orang-utan genomes (vol 469, pg 529, 2011)

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NATURE 2022年第7924期608卷 E36-E36页

作者： Locke, Devin P. Hillier, LaDeana W. Warren, Wesley C. Worley, Kim C. Nazareth, Lynne V. Muzny, Donna M. Yang, Shiaw-Pyng Wang, Zhengyuan Chinwalla, Asif T. Minx, Pat Mitreva, Makedonka Cook, Lisa Delehaunty, Kim D. Fronick, Catrina Schmidt, Heather Fulton, Lucinda A. Fulton, Robert S. Nelson, Joanne O. Magrini, Vincent Pohl, Craig Graves, Tina A. Markovic, Chris Cree, Andy Dinh, Huyen H. Hume, Jennifer Kovar, Christie L. Fowler, Gerald R. Lunter, Gerton Meader, Stephen Heger, Andreas Ponting, Chris P. Marques-Bonet, Tomas Alkan, Can Chen, Lin Cheng, Ze Kidd, Jeffrey M. Eichler, Evan E. White, Simon Searle, Stephen Vilella, Albert J. Chen, Yuan Flicek, Paul Ma, Jian Raney, Brian Suh, Bernard Burhans, Richard Herrero, Javier Haussler, David Faria, Rui Fernando, Olga Darre, Fleur Farre, Domenec Gazave, Elodie Oliva, Meritxell Navarro, Arcadi Roberto, Roberta Capozzi, Oronzo Archidiacono, Nicoletta Della Valle, Giuliano Purgato, Stefania Rocchi, Mariano Konkel, Miriam K. Walker, Jerilyn A. Ullmer, Brygg Batzer, Mark A. Smit, Arian F. A. Hubley, Robert Casola, Claudio Schrider, Daniel R. Hahn, Matthew W. Quesada, Victor Puente, Xose S. Ordonez, Gonzalo R. Lopez-Otin, Carlos Vinar, Tomas Brejova, Brona Ratan, Aakrosh Harris, Robert S. Miller, Webb Kosiol, Carolin Lawson, Heather A. Taliwal, Vikas Martins, Andre L. Siepel, Adam RoyChoudhury, Arindam Ma, Xin Degenhardt, Jeremiah Bustamante, Carlos D. Gutenkunst, Ryan N. Mailund, Thomas Dutheil, Julien Y. Hobolth, Asger Schierup, Mikkel H. Ryder, Oliver A. Yoshinaga, Yuko de Jong, Pieter J. Weinstock, George M. Rogers, Jeffrey Mardis, Elaine R. Gibbs, Richard A. Wilson, Richard K. The Genome Center at Washington University Washington University School of Medicine Saint Louis Missouri USA Human Genome Sequencing Center Department of Molecular and Human Genetics Baylor College of Medicine One Baylor Plaza Houston Texas USA MRC Functional Genomics Unit and Department of Physiology Anatomy and Genetics University of Oxford Le Gros Clark Building Oxford UK Wellcome Trust Centre for Human Genetics Oxford UK Department of Genome Sciences University of Washington School of Medicine Seattle Washington USA IBE Institut de Biologia Evolutiva (UPF-CSIC) Universitat Pompeu Fabra PRBB Doctor Aiguader 88 Barcelona Spain Howard Hughes Medical Institute Seattle Washington USA CIBIO Centro de Investigação em Biodiversidade e Recursos Genéticos Universidade do Porto Campus Agrário de Vairão Vairão Portugal Instituto de Tecnologia Química e Biológica Universidade Nova de Lisboa Oeiras Portugal ICREA (Institució Catalana de Recerca i Estudis Avançats) and INB (Instituto Nacional de Bioinformática) PRBB Doctor Aiguader 88 Barcelona Spain Wellcome Trust Sanger Institute Wellcome Trust Genome Campus Cambridge UK European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton Cambridge UK Center for Biomolecular Science and Engineering University of California Santa Cruz California USA Center for Comparative Genomics and Bioinformatics Penn State University University Park Pennsylvania USA Department of Biology University of Bari Bari Italy Department of Biology University of Bologna Bologna Italy Department of Biological Sciences Louisiana State University Baton Rouge Louisiana USA Center for Computation and Technology Department of Computer Sciences Louisiana State University Baton Rouge Louisiana USA Institute for Systems Biology Seattle Washington USA Department of Biology and School of Informatics and Computing Indiana University Bloomington Indiana USA Instituto Universitario de Oncologia Departamento de Bioquimica y Biol

Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 2 — Ex vivo imaging: added value and acquisition

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arXiv 2022年

作者： Schilling, Kurt G. Grussu, Francesco Ianus, Andrada Hansen, Brian Howard, Amy F.D. Barrett, Rachel L.C. Aggarwal, Manisha Michielse, Stijn Nasrallah, Fatima Syeda, Warda Wang, Nian Veraart, Jelle Roebroeck, Alard Bagdasarian, Andrew F. Eichner, Cornelius Sepehrband, Farshid Zimmermann, Jan Soustelle, Lucas Bowman, Christien Tendler, Benjamin C. Hertanu, Andreea Jeurissen, Ben Verhoye, Marleen Frydman, Lucio de Looij, Yohan van Hike, David Dunn, Jeff F. Miller, Karla Landman, Bennett A. Shemesh, Noam Anderson, Adam McKinnon, Emilie Farquharson, Shawna Acqua, Flavio Dell Pierpaoli, Carlo Drobnjak, Ivana Leemans, Alexander Harkins, Kevin D. Descoteaux, Maxime Xu, Duan Huang, Hao Santin, Mathieu D. Grant, Samuel C. Obenaus, Andre Kim, Gene S. Wu, Dan Le Bihan, Denis Blackband, Stephen J. Ciobanu, Luisa Fieremans, Els Bai, Ruiliang Leergaard, Trygve B. Zhang, Jiangyang Dyrby, Tim B. Allan Johnson, G. Cohen-Adad, Julien Budde, Matthew D. Jelescu, Ileana O. Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN United States Vanderbilt University Institute of Imaging Science Vanderbilt University NashvilleTN United States Radiomics Group Vall d’Hebron Institute of Oncology Vall d’Hebron Barcelona Hospital Campus Barcelona Spain Queen Square MS Centre Queen Square Institute of Neurology Faculty of Brain Sciences University College London London United Kingdom Champalimaud Research Champalimaud Foundation Lisbon Portugal Center of Functionally Integrative Neuroscience Aarhus University Aarhus Denmark Department of Bioengineering Imperial College London London United Kingdom FMRIB Centre Wellcome Centre for Integrative Neuroimaging Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom Department of Neuroimaging Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom NatBrainLab Department of Forensics and Neurodevelopmental Sciences Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University School of Medicine BaltimoreMD United States Maastricht University Medical Center Maastricht Netherlands The Queensland Brain Institute The University of Queensland Queensland Australia Melbourne Neuropsychiatry Centre The University of Melbourne ParkvilleVIC Australia Department of Radiology and Imaging Sciences Indiana University IN United States Stark Neurosciences Research Institute Indiana University School of Medicine IN United States Center for Biomedical Imaging NYU Grossman School of Medicine New YorkNY United States Faculty of psychology and Neuroscience Maastricht University Maastricht Netherlands Department of Chemical & Biomedical Engineering FAMU-FSU College of Engineering Florida State University TallahasseeFL United States Center for Interdisciplinary Magnetic Re

The value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher signal-to-noise ratio (SNR) and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents "Part 2" of a 3-part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge. © 2022, CC BY.

关键词： Image acquisition

Head versus heart: social media reveals differential language of loneliness from depression

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Npj mental health research 2022年第1期1卷 16页

作者： Tingting Liu Lyle H Ungar Brenda Curtis Garrick Sherman Kenna Yadeta Louis Tay Johannes C Eichstaedt Sharath Chandra Guntuku National Institute on Drug Abuse (NIDA IRP) National Institutes of Health (NIH) Baltimore MD USA. tingting.liu@nih.gov. Positive Psychology Center University of Pennsylvania Philadelphia PA USA. tingting.liu@nih.gov. Positive Psychology Center University of Pennsylvania Philadelphia PA USA. Department of Computer and Information Science University of Pennsylvania Philadelphia PA USA. National Institute on Drug Abuse (NIDA IRP) National Institutes of Health (NIH) Baltimore MD USA. Department of Psychological Sciences Purdue University West Lafayette IN USA. Department of Psychology Institute for Human-Centered A.I. Stanford University Stanford CA USA. Department of Computer and Information Science University of Pennsylvania Philadelphia PA USA. sharathg@cis.upenn.edu.

We study the language differentially associated with loneliness and depression using 3.4-million Facebook posts from 2986 individuals, and uncover the statistical associations of survey-based depression and loneliness with both dictionary-based (Linguistic Inquiry Word Count 2015) and open-vocabulary linguistic features (words, phrases, and topics). Loneliness and depression were found to have highly overlapping language profiles, including sickness, pain, and negative emotions as (cross-sectional) risk factors, and social relationships and activities as protective factors. Compared to depression, the language associated with loneliness reflects a stronger cognitive focus, including more references to cognitive processes (i.e., differentiation and tentative language, thoughts, and the observation of irregularities), and cognitive activities like reading and writing. As might be expected, less lonely users were more likely to reference social relationships (e.g., friends and family, romantic relationships), and use first-person plural pronouns. Our findings suggest that the mechanisms of loneliness include self-oriented cognitive activities (i.e., reading) and an overattention to the interpretation of information in the environment. These data-driven ecological findings suggest interventions for loneliness that target maladaptive social cognitions (e.g., through reframing the perception of social environments), strengthen social relationships, and treat other affective distress (i.e., depression).

关键词： Psychology Depression Risk factors computer science

A framework and resource for global collaboration in non-human primate neuroscience

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Current Research in Neurobiology 2023年 4卷 100079页

作者： Hartig, Renée Klink, P. Christiaan Polyakova, Zlata Dehaqani, Mohammad-Reza A. Bondar, Igor Merchant, Hugo Vanduffel, Wim Roe, Anna Wang Nambu, Atsushi Thirumala, M. Shmuel, Amir Kapoor, Vishal Gothard, Katalin M. Evrard, Henry C. Basso, Michele A. Petkov, Christopher I. Mitchell, Anna S. Max Planck Institute for Biological Cybernetics Max-Planck-Ring 11 Tübingen 72076 Germany Functional and Comparative Neuroanatomy Laboratory Werner Reichardt Centre for Integrative Neuroscience Eberhard Karls University of Tübingen Otfried-Müller-Straße 25 Tübingen 72076 Germany Department of Psychiatry and Psychotherapy University Medical Center Johannes Gutenberg-University Mainz 55131 Germany Nathan S. Kline Institute for Psychiatric Research Center for Biomedical Imaging and Neuromodulation Orangeburg New York 10962 United States Department of Vision and Cognition Netherlands Institute for Neuroscience Royal Netherlands Academy of Arts and Sciences Meibergdreef 47 Amsterdam 1105 BA Netherlands Laboratory of Visual Brain Therapy Sorbonne Université Institut National de la Santé et de la Recherche Médicale Centre National de la Recherche Scientifique Institut de la Vision Paris F-75012 France Experimental Psychology Helmholtz institute Utrecht University Heidelberglaan 1 Utrecht 3584 CS Netherlands Center for Human Nature Artificial Intelligence and Neuroscience Hokkaido University Sapporo 060-0812 Japan School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran Department of Brain and Cognitive Sciences Cell Science Research Center Royan Institute for Stem Cell Biology and Technology ACECR Tehran Iran Institute of Higher Nervous Activity and Neurophysiology Russian Academy of Sciences Moscow Russian Federation Institute of Neurobiology Universidad Nacional Autónoma de México Campus Juriquilla Department of Neurophysiology Querétaro 76230 Mexico Laboratory for Neuro- and Psychophysiology Department of Neurosciences KU Leuven Medical School Leuven 3000 Belgium Leuven Brain Institute KU Leuven Leuven 3000 Belgium Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlest

As science and technology evolve, there is an increasing need for promotion of international scientific exchange. Collaborations, while offering substantial opportunities for scientists and benefit to society, also present challenges for those working with animal models, such as non-human primates (NHPs). Diversity in regulation of animal research is sometimes mistaken for the absence of common international welfare standards. Here, the ethical and regulatory protocols for 13 countries that have guidelines in place for biomedical research involving NHPs were assessed with a focus on neuroscience. Review of the variability and similarity in trans-national NHP welfare regulations extended to countries in Asia, Europe and North America. A tabulated resource was established to advance solution-oriented discussions and scientific collaborations across borders. Our aim is to better inform the public and other stakeholders. Through cooperative efforts to identify and analyze information with reference to evidence-based discussion, the proposed key ingredients may help to shape and support a more informed, open framework. This framework and resource can be expanded further for biomedical research in other countries. © 2023

关键词： Ethics Macaque Marmoset Regulations Requirements Welfare