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CORRIGENDUM “Metabolic abnormality in the right dorsolateral prefrontal cortex in patients with obsessive-compulsive disorder: proton magnetic resonance spectroscopy”;[Acta Neuropsychiatr 2017;29(3):164-169]

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Acta Neuropsychiatrica 2018年第2期30卷 123-123页

作者： Shin-Eui Park Nam-Gil Choi Gwang-Woo Jeong Interdisciplinary Program of Biomedical Engineering Chonnam National University Gwangju Republic of Korea Department of Radiology Dong Shin University Naju Republic of Korea Department of Radiology Chonnam National University Medical School Gwangju Republic of Korea

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Correction to: Psoralen alleviates radiation-induced bone injury by rescuing skeletal stem cell stemness through AKT mediated up-regulation of GSK-3β and NRF2

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Stem cell research & therapy 2022年第1期13卷 361页

作者： Bo-Feng Yin Zhi-Ling Li Zi-Qiao Yan Zheng Guo Jia-Wu Liang Qian Wang Zhi-Dong Zhao Pei-Lin Li Rui-Cong Hao Meng-Yue Han Xiao-Tong Li Ning Mao Li Ding Da-Fu Chen Yue Gao Heng Zhu Beijing Institute of Radiation Medicine Road Taiping 27 Beijing 100850 People's Republic of China. Beijing Key Laboratory for Radiobiology Beijing Institute of Radiation Medicine Beijing 100850 People's Republic of China. People's Liberation Army General Hospital Road Fuxing 28 Beijing 100853 People's Republic of China. Medical Center of Air Forces PLA Road Fucheng 30 Beijing 100142 People's Republic of China. Graduate School of Anhui Medical University 81 Meishan Road Shushan Qu Hefei 230032 Anhui People's Republic of China. Beijing Institute of Basic Medical Sciences Road Taiping 27 Beijing 100850 People's Republic of China. Beijing Institute of Radiation Medicine Road Taiping 27 Beijing 100850 People's Republic of China. dingli7578@***. Medical Center of Air Forces PLA Road Fucheng 30 Beijing 100142 People's Republic of China. dingli7578@***. Laboratory of Bone Tissue Engineering Beijing Laboratory of Biomedical Materials Beijing Research Institute of Traumatology and Orthopaedics Beijing Jishuitan Hospital Eastern Street Xinjiekou 31 Beijing 100035 China. chendafugo@***. Beijing Institute of Radiation Medicine Road Taiping 27 Beijing 100850 People's Republic of China. gaoyue@***. Beijing Institute of Radiation Medicine Road Taiping 27 Beijing 100850 People's Republic of China. zhudingdingabc@***. Beijing Key Laboratory for Radiobiology Beijing Institute of Radiation Medicine Beijing 100850 People's Republic of China. zhudingdingabc@***. Graduate School of Anhui Medical University 81 Meishan Road Shushan Qu Hefei 230032 Anhui People's Republic of China. zhudingdingabc@***. Beijing Institute of Basic Medical Sciences Road Taiping 27 Beijing 100850 People's Republic of China. zhudingdingabc@***.

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Obtaining accurate probabilistic causal inference by post-processing calibration

arXiv

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arXiv 2017年

作者： Jabbari, Fattaneh Naeini, Mahdi Pakdaman Cooper, Gregory F. Intelligent Systems Program University of Pittsburgh PittsburghPA United States Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Department of Biomedical Informatics University of Pittsburgh PittsburghPA United States

Discovery of an accurate causal Bayesian network structure from observational data can be useful in many areas of science. Often the discoveries are made under uncertainty, which can be expressed as probabilities. To guide the use of such discoveries, including directing further investigation, it is important that those probabilities be well-calibrated. In this paper, we introduce a novel framework to derive calibrated probabilities of causal relationships from observational data. The framework consists of three components: (1) an approximate method for generating initial probability estimates of the edge types for each pair of variables, (2) the availability of a relatively small number of the causal relationships in the network for which the truth status is known, which we call a calibration training set, and (3) a calibration method for using the approximate probability estimates and the calibration training set to generate calibrated probabilities for the many remaining pairs of variables. We also introduce a new calibration method based on a shallow neural network. Our experiments on simulated data support that the proposed approach improves the calibration of causal edge predictions. The results also support that the approach often improves the precision and recall of predictions. Copyright © 2017, The Authors. All rights reserved.

关键词： Calibration

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Digital is the New Blood: Enabling the Present and the Future

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Alzheimer's & Dementia 2023年第S21期19卷

作者： Rhoda Au Zachary T Popp Spencer Low Phillip H Hwang Ileana De Anda-Duran Stephanie Li Salman Rahman Huitong Ding Akwaugo Igwe Cody Karjadi Ting Fang Alvin Ang Sherral A. Devine Ashita S Gurnani Jesse B. Mez Lindsay A. Farrer Preeti Sunderaraman Honghuang Lin Vijaya B. Kolachalama Boston University School of Public Health Boston MA USA Framingham Heart Study Boston University School of Medicine Boston MA USA Davos Alzheimer’s Collaborative Philadelphia PA USA Department of Epidemiology Boston University School of Public Health Boston MA USA Boston University Chobanian & Avedisian School of Medicine Boston MA USA Department of Neurology Boston University Chobanian & Avedisian School of Medicine Boston MA USA Boston University Alzheimer’s Disease Research Center Boston University Chobanian & Avedisian School of Medicine Boston MA USA Department of Anatomy and Neurobiology Boston University Chobanian & Avedisian School of Medicine Boston MA USA Framingham Heart Study Boston University Chobanian & Avedisian School of Medicine Boston MA USA Boston University School of Public Heatlh Boston MA USA Tulane School of Public Health and Tropical Medicine New Orleans LA USA Slone Epidemiology Center Boston University Chobanian & Avedisian School of Medicine Boston MA USA Framigham Heart Study - Boston University Framingham MA USA Boston University Bioinformatics Program Boston MA USA Departments of Medicine (Biomedical Genetics) Neurology Ophthalmology Biostatistics and Epidemiology Boston University Schools of Medicine and Public Health Boston MA USA Department of Neurology - Boston University Chobanian & Avedisian School of Medicine Boston MA USA University of Massachusetts Medical School Worcester MA USA Framingham Heart Study/Boston University BOSTON MA USA Hariri Institute for Computing and Computational Science & Engineering Boston University Boston MA USA College of Arts & Sciences Boston University Boston MA USA Faculty of Computing & Data Sciences Boston University Boston MA USA Boston University Alzheimer’s Disease Center Boston University Chobanian & Avedisian School of Medicine Boston MA USA Whitaker Cardiovascular Institute Boston University Chobanian & Avedisian School of Medicine Boston MA USA

Background Digital is the new blood, where collection, use, and storage of raw digital data streams enabled by technology-embedded sensors are replacing analog methods. Analyses of digital data extend beyond current applications, analogous to previously stored blood currently be used for omics/biomarker research. Today digital technologies are used to measure Alzheimer’s disease (AD)-related clinical symptoms (e.g., cognition, function, and behavior), but future possibilities remain to be determined. Importantly, digital data collection can go beyond current intermittent sampling by employing internet-connected applications and devices that allow real-time monitoring and accurate detection of changes, even within a widely heterogeneous spectrum. Method Beginning in 2005, the Framingham Heart Study (FHS) began digitally recording participants’ spoken responses to neuropsychological (NP) test questions, and in 2011 extended to a digital pen to record written responses. The emergence of wearable devices and smartphone applications has led to an expanded use of digital technologies beyond recordings during NP assessments. The Boston University Alzheimer’s Disease Research Center (BU ADRC) leverages digital sensors in multiple internet-connected devices that longitudinally collect digital data, in both in-person and remote settings. Result The first publication involving FHS digital data was in 2016; the remaining (n> 17) have been from 2020-current. Digital data measuring cognition, function and behavior are being collected through the BU ADRC, where results to date indicate nearly 100% and 75% uptake of active and passive engagement applications, respectively, and 95% uptake for wearable devices (n = 60). Longitudinal assessments include > 3 months for ∼50 participants; > 1 year for n∼21 participants. Conclusion Opportunities for improved trial outcome measurement are evident in the broad range of outcomes digital sensors capture beyond traditional research methodologi

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Mechanomyography signals in spastic muscle and the correlation with the modified Ashworth scale

Mechanomyography signals in spastic muscle and the correlati...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： E. L. Santos M. C. Santos E. Krueger G. N. Nogueira-Neto P. Nohama Biomedical Engineering at the Graduate Program in Electrical and Computer Engineering Federal Technological University of Paraná - (CPGEI-UTFPR) Curitiba/PR Brazil Biomedical Engineering at the Graduate Program in Biomedical Engineering Federal Technological University of Paraná - (PPGEB-UTFPR) Biomedical Engineering UTFPR Curitiba PR Brazil Anatomy department Londrina State University Electrical Engineering Pontifical Catholic University of Paraná (PUCPR) Curitiba PR Brazil Electrical Engineering UTFPR and PUCPR Curitiba PR Brazil

ISBN: (纸本)9781457702198

The modified Ashworth scale (MAS) is the most widely used measurement technique to assess levels of spasticity. In MAS, the evaluator graduates spasticity considering his/her subjective analysis of the muscular endurance during passive stretching. Therefore, it is a subjective scale. Mechanomyography (MMG) allows registering the vibrations generated by muscle contraction and stretching events that propagate through the tissue until the surface of the skin. With this in mind, this study aimed to investigate possible correlations between MMG signal and muscle spasticity levels determined by MAS. We evaluated 34 limbs considered spastic by MAS, including upper and lower limbs of 22 individuals of both sexes. Simultaneously, the MMG signals of the spastic muscle group (agonists) were acquired. The features investigated involved, in the time domain, the median energy (MMGME) of the MMG Z-axis (perpendicular to the muscle fibers) and, in the frequency domain, the median frequency (MMG mf ). The Kruskal-Wallis test (pme. There was a high linear correlation between the MMG me and MAS (R 2 =0.9557) and also a high correlation as indicated by Spearman test (ρ=0.9856; pmf did not present significant differences between MAS spasticity levels. There was moderate linear correlation between MAS and MMG mf (R 2 =0.4883 and Spearman test [ρ = 0.4590; p

关键词： Muscles Correlation Skin Spectral analysis biomedical engineering Elbow Vibrations

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Fat percentage evaluation through portable ultrasound in adolescents: A comparison with dual energy X-ray absorptiometry

Fat percentage evaluation through portable ultrasound in ado...

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IEEE EMBS Conference on biomedical engineering and Sciences (IECBES)

作者： Wagner Luis Ripka Pedro Miguel Gewehr Leandra Ulbricht Graduate Program in Electrical and Computer Engineering Federal University of Technology - Paraná Curitiba Brazil Graduate Program in Biomedical Engineering Federal University of Technology - Paraná Curitiba Brazil

ISBN: (纸本)9781467377928

Ultrasound has been pointed as a low cost and extremely practical new tool for monitoring body composition and obesity. Thus, this study aims at analyzing the performance of portable US, in comparison with dual energy X-ray absorptiometry (DXA) reference method, in specific equations for predicting fat percentage on male adolescents. 143 male adolescents aged from 12 to 17 years old were evaluated and data on corporal mass, height and fat percentage were collected by US (%BF US) and DXA (%BF). The initial evaluation showed an under estimation of the US method (mean = 10.57 % and standard deviation = 4.45%) in comparison with DXA reference method (mean = 19.94 % and standard deviation = 5.36%). The creation of a specific model, developed from the US measurements, allowed values of R 2 = 0.853 with standard error of the estimate = 1.49. Bland-Altman concordance graphic analysis did not present significant bias. Results suggest that it is possible to use portable US technology to evaluate fat percentage in adolescents, provided that a specific mathematical modeling is used.

关键词： Fats Mathematical model Ultrasonic imaging Obesity Pediatrics Correlation Standards

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Author Correction: Drug response in organoids generated from frozen primary tumor tissues

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Scientific reports 2019年第1期9卷 6517页

作者： Alex J Walsh Rebecca S Cook Melinda E Sanders Carlos L Arteaga Melissa C Skala Department of Biomedical Engineering Vanderbilt University Station B Box 1631 Nashville Tennessee 37235 USA. Department of Cancer Biology Vanderbilt University 2220 Pierce Avenue Nashville Tennessee USA. Breast Cancer Research Program Vanderbilt- Ingram Cancer Center Vanderbilt University Nashville USA. Department of Pathology Microbiology & Immunology Vanderbilt University Medical Center 1301 Medical Center Drive 4918-A TVC Building Nashville Tennessee 37232 USA. Department of Medicine Vanderbilt University 2220 Pierce Avenue Nashville Tennessee USA. Department of Biomedical Engineering Vanderbilt University Station B Box 1631 Nashville Tennessee 37235 USA. m.skala@vanderbilt.edu. Department of Cancer Biology Vanderbilt University 2220 Pierce Avenue Nashville Tennessee USA. m.skala@vanderbilt.edu. Breast Cancer Research Program Vanderbilt- Ingram Cancer Center Vanderbilt University Nashville USA. m.skala@vanderbilt.edu.

A correction has been published and is appended to both the HTML and PDF versions of this paper. The error has not been fixed in the paper.

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A rapid microfluidic stamping device for studying cardiac stem cells and endothelial cells co-culture 20

A rapid microfluidic stamping device for studying cardiac st...

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20th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2016

作者： Barforoushi, A.H. Shemesh, J. Farbehi, N. Asadnia, M. Yeoh, G.H. Nordon, R.E. Warkiani, M.E. School of Mechanical and Manufacturing Engineering Australian Centre for NanoMedicine University of New South Wales Sydney Australia Graduate School of Biomedical Engineering University of New South Wales Australia Department of Engineering Faculty of Science Macquarie University Sydney Australia

ISBN: (纸本)9780979806490

Many biological processes in the body are regulated by synchronized activity between two cell types. Recent advances in cell μcontact printing have facilitated the in-vitro study of homotypic and heterotypic cell-cell interaction. However, these techniques are still complicated to perform and are seldom used by biologists. We report here development of a novel microfluidic stamping device for patterning two adherent cell lines with well-defined interlacing configurations to study cell-cell spatial interactions. To demonstrate the stamp's capabilities, we developed an in-vitro model of endothelial and cardiac mesenchymal stem cell interactions, which are thought to regulate coronary repair after myocardial injury.

关键词： Stem cells

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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Lipopolysaccharide from Gut-Associated Lymphoid-Tissue-ResidentAlcaligenes faecalis: Complete Structure Determination and Chemical Synthesis of Its Lipid A

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Angewandte Chemie 2021年第18期133卷

作者： Dr. Atsushi Shimoyama Dr. Flaviana Di Lorenzo Haruki Yamaura Dr. Keisuke Mizote Dr. Angelo Palmigiano Molly D. Pither Dr. Immacolata Speciale Tomoya Uto Dr. Seiji Masui Dr. Luisa Sturiale Prof. Domenico Garozzo Dr. Koji Hosomi Dr. Naoko Shibata Dr. Kazuya Kabayama Prof. Yukari Fujimoto Prof. Alba Silipo Prof. Jun Kunisawa Prof. Hiroshi Kiyono Prof. Antonio Molinaro Prof. Koichi Fukase Department of Chemistry Graduate School of Science Osaka University 1-1 Machikaneyama Toyonaka Osaka 560-0043 Japan Project Research Center for Fundamental Sciences Osaka University 1-1 Machikaneyama Toyonaka Osaka 560-0043 Japan Department of Chemical Sciences and Task Force on Microbiome Studies University of Naples Federico II Via Cinthia 4 80126 Naples Italy CNR Institute for Polymers Composites and Biomaterials IPCB Via P. Gaifami 18 95126 Catania Italy Department of Chemical Sciences University of Naples Federico II Via Cinthia 4 80126 Naples Italy Laboratory of Vaccine Materials Center for Vaccine and Adjuvant Research and Laboratory of Gut Environmental System National Institutes of Biomedical Innovation Health and Nutrition Osaka 567-0085 Japan Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku-ku Tokyo 169-8555 Japan Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa 223-8522 Japan International Research and Development Center for Mucosal Vaccines The Institute of Medical Science The University of Tokyo 4–6-1 Shirokanedai Minato-ku Tokyo 108-8639 Japan

Alcaligenes faecalis is the predominant Gram-negative bacterium inhabiting gut-associated lymphoid tissues, Peyer's patches. We previously reported that an A. faecalis lipopolysaccharide (LPS) acted as a weak agonist for Toll-like receptor 4 (TLR4)/myeloid differentiation factor-2 (MD-2) receptor as well as a potent inducer of IgA without excessive inflammation, thus suggesting that A. faecalis LPS might be used as a safe adjuvant. In this study, we characterized the structure of both the lipooligosaccharide (LOS) and LPS from A. faecalis . We synthesized three lipid A molecules with different degrees of acylation by an efficient route involving the simultaneous introduction of 1- and 4′-phosphates. Hexaacylated A. faecalis lipid A showed moderate agonistic activity towards TLR4-mediated signaling and the ability to elicit a discrete interleukin-6 release in human cell lines and mice. It was thus found to be the active principle of the LOS/LPS and a promising vaccine adjuvant candidate.

关键词： glycolipids lipid A lipopolysaccharides oligosaccharides vaccines

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