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Deep learning models to detect hidden clinical correlates

The Lancet. Digital health 2020年第7期2卷 e334-e335页

作者： David Ouyang James Zou Department of Medicine Stanford University Palo Alto CA 94025 USA. Electronic address: Ouyangd@stanford.edu. Department of Biomedical Data Science Computer Science and Electrical Engineering Stanford University Palo Alto CA 94025 USA.

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Contrastive functional connectivity defines neurophysiology-informed symptom dimensions in major depression

Cell reports. Medicine

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Cell reports. Medicine 2025年 102151页

作者： Hao Zhu Xiaoyu Tong Nancy B Carlisle Hua Xie Corey J Keller Desmond J Oathes Feng Liu Charles B Nemeroff Gregory A Fonzo Yu Zhang Department of Bioengineering Lehigh University Bethlehem PA USA. Department of Psychology Lehigh University Bethlehem PA USA. Center for Neuroscience Research Children's National Hospital Washington DC USA. Wu Tsai Neuroscience Institute Stanford University Stanford CA USA Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford CA USA Veterans Affairs Palo Alto Healthcare System and the Sierra Pacific Mental Illness Research Education and Clinical Center (MIRECC) Palo Alto CA USA. Center for Brain Imaging and Stimulation Department of Psychiatry University of Pennsylvania Perelman School of Medicine Philadelphia PA USA Center for Neuromodulation in Depression and Stress Department of Psychiatry University of Pennsylvania Perelman School of Medicine Philadelphia PA USA Penn Brain Science Translation Innovation and Modulation Center University of Pennsylvania Perelman School of Medicine Philadelphia PA USA Departments of Neurology Neurosurgery Bioengineering and Neuroscience University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Systems and Enterprises Stevens Institute of Technology Hoboken NJ USA. Center for Psychedelic Research and Therapy Department of Psychiatry and Behavioral Sciences Dell Medical School The University of Texas at Austin Austin TX USA. Department of Bioengineering Lehigh University Bethlehem PA USA Department of Electrical and Computer Engineering Lehigh University Bethlehem PA USA. Electronic address: yuzi20@lehigh.edu.

Major depressive disorder (MDD) is highly heterogeneous, posing challenges for effective treatment due to complex interactions between clinical symptoms and neurobiological features. To address this, we apply contrastive principal-component analysis to fMRI-based resting-state functional connectivity, isolating disorder-specific variations by contrasting data from 233 MDD patients and 285 healthy controls. Subsequently, we use sparse canonical correlation analysis to identify two significant dimensions linking distinct brain circuits with clinical profiles. One dimension relates to an internalizing-externalizing symptom spectrum involving visual and limbic networks and is associated with cognitive task reaction times. The other dimension, linked to personality traits protective against depression (e.g., extraversion), is driven by dorsal attention network connections and correlates with cognitive control and psychomotor performance. This approach illuminates stable symptom dimensions and their neurophysiological underpinnings, aiding in precision phenotyping for MDD and supporting the development of targeted, individualized therapeutic strategies for mental health care.

关键词： brain-symptom dimension contrastive machine learning disease heterogeneity fMRI functional connectivity major depressive disorder

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Corrigendum to "Dissemination in time and space in presymptomatic granulin mutation carriers: A spatial chronnectome study" [Neurobiology of Aging Volume 108, December 2021, Pages 155-167]

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Neurobiology of aging 2022年 119卷 140-144页

作者： Enrico Premi Marcello Giunta Armin Iraji Srinivas Rachakonda VinceD Calhoun Stefano Gazzina Alberto Benussi Roberto Gasparotti Silvana Archetti Martina Bocchetta Dave Cash Emily Todd Georgia Peakman Rhian Convery John C van Swieten Lize Jiskoot Raquel Sanchez-Valle Fermin Moreno Robert Laforce Caroline Graff Matthis Synofzik Daniela Galimberti JamesB Rowe Mario Masellis Carmela Tartaglia Elizabeth Finger Rik Vandenberghe Alexandre de Mendonça Fabrizio Tagliavini Chris R Butler Isabel Santana Alexander Gerhard Isabelle Le Ber Florence Pasquier Simon Ducharme Johannes Levin Adrian Danek Sandro Sorbi Markus Otto Jonathan D Rohrer Barbara Borroni Stroke Unit Azienda Socio Sanitaria Territoriale Spedali Civili Brescia Brescia Italy. Centre for Neurodegenerative Disorders Department of Clinical and Experimental Sciences University of Brescia Brescia Italy. Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University Georgia Institute of Technology Emory University Atlanta GA USA. Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University Georgia Institute of Technology Emory University Atlanta GA USA Departments of Psychology and Computer Science Georgia State University Atlanta GA USA Department of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA. Neurophysiology Unit Azienda Socio Sanitaria Territoriale Spedali Civili Brescia Brescia Italy. Neuroradiology Unit University of Brescia Brescia Italy. Laboratory Unit Azienda Socio Sanitaria Territoriale Spedali Civili Brescia Brescia Italy. Department of Neurodegenerative Disease Dementia Research Centre UCL Institute of Neurology Queen Square London UK. Department of Neurology Erasmus Medical Centre Rotterdam the Netherlands. Alzheimer's disease and Other Cognitive Disorders Unit Neurology Service Hospital Clinic University of Barcelona Barcelona Spain. Cognitive Disorders Unit Department of Neurology Donostia University Hospital San Sebastian Gipuzkoa Spain. Clinique Interdisciplinaire de Memoire Department des Sciences Neurologiques CHU de Quebec and Faculte de Medecine Universite Laval Quebec Canada. Center for Alzheimer Research Division of Neurogeriatrics Department of Neurobiology Care Sciences and Society Bioclinicum Karolinska Institutet Solna Sweden. Department of Neurodegenerative Diseases Hertie-Institute for Clinical Brain Research and Center of Neurology University of Tubingen Tubingen Germany. Fondazione Ca' Granda IRCCS Ospedale Policlinico Milan Italy University of Milan

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Corrigendum to "Design and implementation of a low-cost, tabletop MRI scanner for education and research prototyping" [J. Magn. Reson. 310 (2020) 106625]

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Journal of magnetic resonance (San Diego, Calif. : 1997) 2020年 317卷 106764页

作者： Clarissa Zimmerman Cooley Jason P Stockmann Thomas Witzel Cris LaPierre Azma Mareyam Feng Jia Maxim Zaitsev Wenhui Yang Wang Zheng Pascal Stang Greig Scott Elfar Adalsteinsson Jacob K White Lawrence L Wald A. A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA Harvard Medical School Boston MA USA. Electronic address: clarissa@nmr.mgh.harvard.edu. Harvard Medical School Boston MA USA. A. A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Charlestown MA USA. Dept. of Radiology Medical Physics Medical Center University of Freiburg Faculty of Medicine University of Freiburg Freiburg Germany. Institute of Electrical Engineering Chinese Academy of Sciences Beijing China. Procyon Engineering San Jose CA USA Department of Electrical Engineering Stanford University Stanford CA USA. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Harvard-MIT Division of Health Sciences Technology Cambridge MA USA. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA. Harvard Medical School Boston MA USA

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Highly Reproducible Formation of a Polymer Single‐Molecule Junction for a Well‐Defined Current Signal

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Angewandte Chemie 2019年第27期131卷

作者： Takanori Harashima Yusuke Hasegawa Satoshi Kaneko Manabu Kiguchi Tomoya Ono Tomoaki Nishino Department of Chemistry School of Science Tokyo Institute of Technology Ookayama Meguro-ku Tokyo 152-8551 Japan Center for Computational Sciences University of Tsukuba Tennodai Tsukuba 305-8577 Japan Present address: Department of Electrical and Electronic Engineering Graduate School of Engineering Kobe University Rokkodai Nada-ku Kobe 657-8501 Japan

Single‐molecule devices attract much interest in the development of nanoscale electronics. Although a variety of functional single molecules for single‐molecule electronics have been developed, there still remains the need to implement sophisticated functionalization toward practical applications. Given its superior functionality encountered in macroscopic materials, a polymer could be a useful building block in the single‐molecule devices. Therefore, a molecular junction composed of polymer has now been created. Furthermore, an automated algorithm was developed to quantitatively analyze the tunneling current through the junction. Quantitative analysis revealed that the polymer junction exhibits a higher formation probability and longer lifetime than its monomer counterpart. These results suggest that the polymer provides a unique opportunity to design both stable and highly functional molecular devices for nanoelectronics.

关键词： Einzelmolekülstudien Molekulare Elektronik Molekulare Geräte Nanotechnologie Polymere

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Corrigendum to "Long-term seizure dynamics are determined by the nature of seizures and the mutual interactions between them" [Neurobiol. Dis., Volume 154 (2021), Article 105,347]

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Neurobiology of disease 2021年 159卷 105484页

作者： Jan Kudlacek Jan Chvojka Vojtech Kumpost Barbora Hermanovska Antonin Posusta John G R Jefferys Matias I Maturana Ondrej Novak Mark J Cook Jakub Otahal Jaroslav Hlinka Premysl Jiruska Department of Physiology Second Faculty of Medicine Charles University Prague Czech Republic Department of Developmental Epileptology Institute of Physiology of the Czech Academy of Sciences Prague Czech Republic Department of Circuit Theory Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic. Department of Developmental Epileptology Institute of Physiology of the Czech Academy of Sciences Prague Czech Republic. Department of Physiology Second Faculty of Medicine Charles University Prague Czech Republic. The Graeme Clark Institute & Department of Medicine St Vincent's Hospital The University of Melbourne Melbourne Australia Seer Medical Melbourne Australia. The Graeme Clark Institute & Department of Medicine St Vincent's Hospital The University of Melbourne Melbourne Australia. Department of Nonlinear Modelling Institute of Computer Science of the Czech Academy of Sciences Prague 182 07 Czech Republic National Institute of Mental Health Klecany Czech Republic. Department of Developmental Epileptology Institute of Physiology of the Czech Academy of Sciences Prague Czech Republic. Electronic address: jiruskapremysl@***.

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Corrigendum to "Dynamics of Inter-Molecular Interactions Between Single Aβ42 Oligomeric and Aggregate Species by High-Speed Atomic Force Microscopy"

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Journal of molecular biology 2020年第2期432卷 633页

作者： Lei Feng Hiroki Watanabe Paul Molino Gordon G Wallace Son L Phung Takayuki Uchihashi Michael J Higgins ARC Centre of Excellence for Electromaterials Science Intelligent Polymer Research Institute AIIM Facility Innovation Campus University of Wollongong Wollongong NSW 2522 Australia. Department of Physics Nagoya University Higashiyama Campus Furo-cho Chikusa-ku Nagoya 464-8602 Japan. School of Electrical Computer and Telecommunications Engineering Faculty of Engineering and Information Sciences University of Wollongong Northfields Avenue Wollongong NSW 2522 Australia. ARC Centre of Excellence for Electromaterials Science Intelligent Polymer Research Institute AIIM Facility Innovation Campus University of Wollongong Wollongong NSW 2522 Australia. Electronic address: mhiggins@uow.edu.au.

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Cover Feature: Pyrolysis of Iron-Containing Polyanilines under Micropore Generation Control: Electrocatalytic Performance in the Oxygen Reduction Reaction (ChemPlusChem 9/2020)

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ChemPlusChem 2020年第9期85卷 1950-1950页

作者： Dr. Quang-Duy Dao Dr. Yuhi Inada Masato Daijo Hitoshi Haneoka Yosuke Murakami Nao Eguchi Dr. Toru Amaya Dr. Takeyuki Suzuki Takafumi Ohkawa Dr. Ryotaro Tsuji Prof. Dr. Toshikazu Hirao Division of Electrical Electronic and Information Engineering Graduate School of Engineering Osaka University Suita Osaka 565-0871 Japan Present address: Faculty of Physics VNU-University of Science Vietnam National University Hanoi Thanhxuan Hanoi 120-034 Vietnam Kyoto Institute of Technology Matsugasaki Kyoto 606-8585 Japan The Institute of Scientific and Industrial Research Osaka University Mihoga-oka Ibaraki Osaka 567-0047 Japan Osaka R&D Laboratory Daihachi Chemical Industry Co. LTD. 3-5-7 Chodo Higashiosaka Osaka 577-0056 Japan Center for Scientific Instrument Renovation and Manufacturing Support Osaka University Mihoga-oka Ibaraki Osaka 567-0047 Japan Department of Applied Chemistry Graduate School of Engineering Osaka University Yamada-oka Suita Osaka 565-0871 Japan KANEKA Fundamental Technology Research Alliance Laboratories Graduate School of Engineering Osaka University Yamada-oka Suita Osaka 565-0871 Japan

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Autofluorescence imaging for improved visualization of joint structures during arthroscopic surgery

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Journal of Experimental Orthopaedics 2017年第1期4卷 19页

作者： Nguyen, Duy Tan van Horssen, Pepijn Derriks, Hans van de Giessen, Martijn van Leeuwen, Ton Present Address: Department of Family Medicine University of Gent Ghent Belgium Department of Orthopaedic Surgery University of Amsterdam Amsterdam Netherlands Department of Physics and Medical Technology VU University Medical Center Amsterdam Netherlands Biomedical Engineering and Physics University of Amsterdam Amsterdam Netherlands Present Address: St. Maartenskliniek Nijmegen Netherlands Department of Radiology Leiden University Medical Center Leiden Netherlands Department of Intelligent Systems Faculty of Electrical Engineering Applied Mathematics and Computer Science Delft University of Technology Delft Netherlands

Background: The purpose of our study is to develop the arthroscopic autofluorescence imaging (AFI) system to improve the visualization during arthroscopic surgery by real-time enhancing the contrast between joint structures with autofluorescence imaging. Its validity was evaluated around the arthroscopic anterior cruciate ligament (ACL) reconstruction, specifically improving the contrast between the femoral insertion site and its background. The feasibility of the AFI system was validated with bovine and human knees. The spectral responses of the femoral insertion site and its surrounding bone and cartilage were measured with a fluorospectrometer. A prototype of the AFI system was developed based on the spectral responses (SR) and test images of the insertion site. The accuracy was validated by evaluating the overlap between manually segmented insertion sites on the white light color images and on the corresponding spectral unmixed autofluorescence images. The final prototype of the AFI system was tested during arthroscopy in cadaveric knees. Results: The results showed that the joint structures have different SRs. Spectral unmixing enabled separation of the SRs and improved the contrast between the joint structures. The agreement between visible light and autofluorescence ligament insertions had a mean Dice coefficient of 0.84 and the mean Dice coefficient of the interobserver variability for visible light imaging was 0.85. Conclusions: We have shown that the femoral insertion site can be accurately visualized with autofluorescence imaging combined with spectral unmixing. The AFI system demonstrates the feasibility of real-time and subject-specific visualization of the femoral insertion site which can facilitate anatomic ACL reconstruction. In addition, the AFI system can facilitate arthroscopic procedures in other joints and can also be used as a diagnostic tool. © 2017, The Author(s).

关键词： Anterior cruciate ligament Arthroscopic autofluorescence imaging system Arthroscopy Fluorescence Fluorescence arthroscope

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Data Mining When Each Data Point is a Network

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Conference on Patterns of Dynamics held in honor of Bernold Fiedler’s 60th Birthday, 2016

作者： Rajendran, Karthikeyan Kattis, Assimakis Holiday, Alexander Kondor, Risi Kevrekidis, Ioannis G. Department of Chemical and Biological Engineering Princeton University Present Address: 731 Lexington Avenue New YorkNY10022 United States Theory Group Department of Computer Science University of Toronto 10 King’s College Road TorontoONM5S 3G4 Canada Department of Chemical and Biological Engineering Princeton University 41 Olden Street PrincetonNJ08544 United States Machine Learning Group Computer Science and Statistics University of Chicago Ryerson 257B 1100 E. 58th Street ChicagoIl60637 United States A319 Engineering Quad Department of Chemical and Biological Engineering Princeton University Technische Universität München - Institute for Advanced Study Zuse Institut Berlin 41 Olden Street PrincetonNJ08544 United States

ISBN: (纸本)9783319641720

We discuss the problem of extending data mining approaches to cases in which data points arise in the form of individual graphs. Being able to find the intrinsic low-dimensionality in ensembles of graphs can be useful in a variety of modeling contexts, especially when coarse-graining the detailed graph information is of interest. One of the main challenges in mining graph data is the definition of a suitable pairwise similarity metric in the space of graphs. We explore two practical solutions to solving this problem: one based on finding subgraph densities, and one using spectral information. The approach is illustrated on three test data sets (ensembles of graphs);two of these are obtained from standard literature graph generating algorithms, while the graphs in the third example are sampled as dynamic snapshots from an evolving network simulation. We further combine these approaches with equation free techniques, demonstrating how such data mining can enhance scientific computation of network evolution dynamics. © Springer International Publishing AG 2017.

关键词： Data mining

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