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MedComm - Biomaterials and Applications 2023年第2期2卷

作者： Li, Ling Nie, Shihong Du, Ting Zhao, Jiaxuan Chen, Xiaoyuan West China School of Public Health West China Fourth Hospital and State Key Laboratory of Biotherapy Sichuan University Chengdu China Department of Radiation Oncology Cancer Center West China Hospital Sichuan University Chengdu China Non-coding RNA and Drug Discovery Key Laboratory of Sichuan Province Chengdu Medical College Chengdu China Departments of Diagnostic Radiology Surgery Chemical and Biomolecular Engineering and Biomedical Engineering Yong Loo Lin School of Medicine and Faculty of Engineering National University of Singapore Singapore Singapore Clinical Imaging Research Centre Centre for Translational Medicine Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Nanomedicine Translational Research Program NUS Center for Nanomedicine Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Agency for Science Technology and Research (A*STAR) Singapore Singapore

DNA origami, a promising branch of structural DNA technology, refers to the technique of folding a single-stranded DNA scaffold into well-defined nanostructures. In recent years, DNA origami nanostructures have shown considerable promise in a variety of biomedical applications, owing to their biodegradability, unique programmability, and addressability. Despite their popularity, the biomedical application of DNA origami techniques, which exploits their unique programmability and addressability, is rare in previous studies. Most recently, mounting evidence has demonstrated the robustness of DNA origami nanostructures in the spatial organization of functional components at the nanoscale in the biomedical field. These examples provide typical paradigms to fully realize the potential of DNA origami techniques by taking advantage of their unique programmability and addressability. This minireview summarizes the recent advancements of DNA origami techniques in biosensing, biocatalysis, and drug delivery, and the representative examples using DNA origami nanostructures for the spatial organization of functional molecules with nanometric precision are highlighted. We further discuss the possible limitations and challenges for in vivo applications, including stability issues and potential immunogenicity, and finally, propose some strategies to overcome these obstacles to fully realize the potential of DNA origami techniques in biomedical applications. © 2023 The Authors. MedComm – Biomaterials and Applications published by John Wiley & Sons Australia, Ltd on behalf of Sichuan International Medical Exchange & Promotion Association (SCIMEA).

关键词： biocatalysis biosensing DNA nanotechnology DNA origami

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PTMD: A Database of Human Disease-associated Post-translational Modifications

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Genomics, Proteomics & Bioinformatics 2018年第4期16卷 244-251页

作者： Haodong Xu Yongbo Wang Shaofeng Lin Wankun Deng Di Peng Qinghua Cui Yu Xue Department of Bioinformatics & Systems Biology MOE Key Laboratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Biomedical Engineering Huazhong University of Science and Technology Department of Biomedical Informatics School of Basic Medical Sciences MOE Key Laboratory of Molecular Cardiovascular Sciences Center for Non-coding RNA Medicine Peking University

Various posttranslational modifications （PTMs） participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently implicated in human diseases. Therefore, an integral resource of PTM–disease associations （PDAs）would be a great help for both academic research and clinical use. In this work, we reported PTMD,a well-curated database containing PTMs that are associated with human diseases. We manually collected 1950 known PDAs in 749 proteins for 23 types of PTMs and 275 types of diseases from the literature. Database analyses show that phosphorylation has the largest number of disease associations, whereas neurologic diseases have the largest number of PTM associations. We classified all known PDAs into six classes according to the PTM status in diseases and demonstrated that the upregulation and presence of PTM events account for a predominant proportion of diseaseassociated PTM events. By reconstructing a disease–gene network, we observed that breast cancers have the largest number of associated PTMs and AKT1 has the largest number of PTMs connected to diseases. Finally, the PTMD database was developed with detailed annotations and can be a useful resource for further analyzing the relations between PTMs and human diseases. PTMD is freely accessible at http：//***.

关键词： Posttranslational modification Phosphorylation PTM-disease association Disease-gene network AKT1

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TP53 loss creates therapeutic vulnerability in colorectal cancer (vol 30, pg 697, 2015)

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NATURE 2021年第7875期597卷 E6-E6页

作者： Liu, Yunhua Zhang, Xinna Han, Cecil Wan, Guohui Huang, Xingxu Ivan, Cristina Jiang, Dahai Rodriguez-Aguayo, Cristian Lopez-Berestein, Gabriel Rao, Pulivarthi H. Maru, Dipen M. Pahl, Andreas He, Xiaoming Sood, Anil K. Ellis, Lee M. Anderl, Jan Lu, Xiongbin Department of Cancer Biology The University of Texas MD Anderson Cancer Center Houston TX USA Department of Gynaecologic Oncology and Reproductive Medicine The University of Texas MD Anderson Cancer Center Houston USA Center for RNA Interference and Non-coding RNAs The University of Texas MD Anderson Cancer Center Houston TX USA Department of Experimental Therapeutics The University of Texas MD Anderson Cancer Center Houston TX USA School of Life Science and Technology ShanghaiTech University Shanghai China Department of Paediatrics Baylor College of Medicine Houston TX USA Department of Pathology The University of Texas MD Anderson Cancer Center Houston TX USA Heidelberg Pharma GmbH Ladenburg Germany Department of Biomedical Engineering The Ohio State University Columbus OH USA Department of Surgical Oncology The University of Texas MD Anderson Cancer Center Houston TX USA

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Biomechanical research using advanced micro-nano devices: In-Vitro cell Characterization focus

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Journal of Advanced Research 2024年

作者： Yan, Shiqiang Lu, Yan An, Changming Hu, Wanglai Chen, Yaofeng Li, Ziwen Wei, Wenbo Chen, Zongzheng Zeng, Xianhai Xu, Wei Lv, Zhenghua Pan, Fan Gao, Wei Wu, Yongyan Shenzhen Institute of Otolaryngology & Key Laboratory of Otolaryngology Longgang Otolaryngology Hospital Guangdong Shenzhen 518172 China Center of Cancer Immunology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen 518055 China Department of Otolaryngology Head & Neck Surgery The First Hospital Jinzhou Medical University Liaoning Jinzhou 121001 China Shanxi Key Laboratory of Otorhinolaryngology Head and Neck Cancer Department of Otolaryngology Head & Neck Surgery First Hospital of Shanxi Medical University Shanxi Taiyuan 030001 China Department of Head and Neck Surgery National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 100021 China Translational Research Institute People's Hospital of Zhengzhou University Academy of Medical Science Henan International Joint Laboratory of Non-coding RNA and Metabolism in Cancer Zhengzhou University Henan Zhengzhou 450003 China Shenzhen University General Hospital & Shenzhen University Clinical Medical Academy Shenzhen University Guangdong Shenzhen 518055 China College of Chemistry & Pharmacy Northwest A&F University Shaanxi Yangling 712100 China The First Affiliated Hospital of Shenzhen University Shenzhen Second People's Hospital Guangdong Shenzhen 518035 China Department of Otolaryngology-Head and Neck Surgery Shandong Provincial ENT Hospital Shandong University Shandong Jinan 250022 China

Background: Cells in the body reside in a dynamic microenvironment subjected to various physical stimuli, where mechanical stimulation plays a crucial role in regulating cellular physiological behaviors and functions. Aim of Review: Investigating the mechanisms and interactions of mechanical transmission is essential for understanding the physiological and functional interplay between cells and physical stimuli. Therefore, establishing an in vitro biomechanical stimulation cell culture system holds significant importance for research related to cellular biomechanics. Key Scientific Concepts of Review: In this review, we primarily focused on various biomechanically relevant cell culture systems and highlighted the advancements and prospects in their preparation processes. Firstly, we discussed the types and characteristics of biomechanics present in the microenvironment within the human body. Subsequently, we introduced the research progress, working principles, preparation processes, potential advantages, applications, and challenges of various biomechanically relevant in vitro cell culture systems. Additionally, we summarized and categorized currently commercialized biomechanically relevant cell culture systems, offering a comprehensive reference for researchers in related fields. © 2024

关键词： Biomechanical stimulation Cell culture systems Cellular biomechanics In vitro models Microenvironment

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A biomarker framework for liver aging: the Aging Biomarker Consortium consensus statement

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Life Medicine 2024年第1期3卷 5页

作者： Aging Biomarker Consortium, Mengmeng Jiang Zhuozhao Zheng Xuan Wang Yanhao Chen Jing Qu Qiurong Ding Weiqi Zhang You-Shuo Liu Jichun Yang Weiqing Tang Yunlong Hou Jinhan He Lin Wang Pengyu Huang Lin-Chen Li Zhiying He Qiang Gao Qian Lu Lai Wei Yan-Jiang Wang Zhenyu Ju Jian-Gao Fan Xiong Zhong Ruan Youfei Guan Guang-Hui Liu Gang Pei Jian Li Yunfang Wang State Key Laboratory of Membrane Biology Institute of Zoology Chinese Academy of Sciences Beijing 100101 China Institute for Stem Cell and Regeneration Chinese Academy of Sciences Beijing 100101 China Department of Radiology Beijing Tsinghua Changgung Hospital School of Clinical Medicine Tsinghua University Beijing 102218 China Hepatopancreatobiliary Center Beijing Tsinghua Changgung Hospital School of Clinical Medicine Tsinghua University Beijing 102218 China CAS Key Laboratory of Nutrition Metabolism and Food Safety Shanghai Institute of Nutrition and Health University of Chinese Academy of Sciences Chinese Academy of Sciences Shanghai 200031 China State Key Laboratory of Stem Cell and Reproductive Biology Institute of Zoology Chinese Academy of Sciences Beijing 100101 China CAS Key Laboratory of Genomic and Precision Medicine Beijing Institute of Genomics Chinese Academy of Sciences and China National Center for Bioinformation Beijing 100101 China Department of Geriatrics the Second Xiangya Hospital and the Institute of Aging and Geriatrics Central South University Changsha 410011 China Department of Physiology and Pathophysiology School of Basic Medical Sciences State Key Laboratory of Vascular Homeostasis and Remodeling Center for Non-coding RNA Medicine Peking University Health Science Center Beijing 100191 China The Key Laboratory of Geriatrics Beijing Institute of Geriatrics Institute of Geriatric Medicine Chinese Academy of Medical Sciences Beijing Hospital/National Center of Gerontology of National Health Commission Beijing 100730 China Yiling Pharmaceutical Academician Workstation Shijiazhuang 050035 China Department of Pharmacy West China Hospital of Sichuan University Chengdu 610041 China Department of Hepatobiliary Surgery Xijing Hospital Fourth Military Medical University Xi?an 710032 China State Key Laboratory of Advanced Medical Materials and Devices Engineering Research Center of Pulmonary and Critical Care Medicine Technology and Device

In human aging, liver aging per se not only increases susceptibility to liver diseases but also increases vulnerability of other organs given its central role in regulating metabolism. Total liver function tends to be well maintained in the healthy elderly, so liver aging is generally difficult to identify early. In response to this critical challenge, the Aging Biomarker Consortium of China has formulated an expert consensus on biomarkers of liver aging by synthesizing the latest scientific literature, comprising insights from both scientists and clinicians. This consensus provides a comprehensive assessment of biomarkers associated with liver aging and presents a systematic framework to characterize these into three dimensions: functional, imaging, and humoral. For the functional domain, we highlight biomarkers associated with cholesterol metabolism and liver-related coagulation function. For the imaging domain, we note that hepatic steatosis and liver blood flow can serve as measurable biomarkers for liver aging. Finally, in the humoral domain, we pinpoint hepatokines and enzymatic alterations worthy of attention. The aim of this expert consensus is to establish a foundation for assessing the extent of liver aging and identify early signs of liver aging-related diseases, thereby improving liver health and the healthy life expectancy of the elderly population.

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The DrugPattern tool for drug set enrichment analysis and its prediction for beneficial effects of oxLDL on type 2 diabetes

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Journal of Genetics and Genomics 2018年第7期45卷 389-397页

作者： Chuanbo Huang Weili Yang Junpei wang Yuan Zhou Bin Geng Georgios Kararigas Jichun Yang Qinghua Cui Department of Biomedical Informatics Department of Physiology and Pathophysiology MOE Key Lab of Cardiovascular Sciences School of Basic Medical Sciences Center for Non-Coding RNA Medicine Peking UniversityBeijing 100191China School of Mathematics Sciences Huaqiao University Quanzhou 362021 China Hypertension Center Fuwai Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeState Key Laboratory of Cardiovascular Disease National Center for Cardiovascular Diseases Beijing 100037 China Charit-Universitatsmedizin Berlin. Corporate Member of Freie Universitat Berlin Humboldt-Universitat zu Berlin Berlin Institute of Health Institute of Gender in Medicine and Center for Cardiovascular Research. DZHK (German Centre for Cardiovascular Research) 10115 Berlin Germany Center of Bioinformatics Key Laboratory for Neuro-lnformation of Ministry of Education School of Life Science and Technology University of Electronic Science and Technology of China Chengdu 610054 China

Enrichment analysis methods, e.g., gene set enrichment analysis, represent one class of important bio- informatical resources for mining patterns in biomedical datasets. However, tools for inferring patterns and rules of a list of drugs are limited. In this study, we developed a web-based tool, DrugPattern, for drug set enrichment analysis. We first collected and curated 7019 drug sets, including indications, adverse reactions, targets, pathways, etc. from public databases. For a list of interested drugs, DrugPat- tern then evaluates the significance of the enrichment of these drugs in each of the 7019 drug sets. To validate DrugPattern, we employed it for the prediction of the effects of oxidized low-density lipoprotein （oxLDL）, a factor expected to be deleterious. We predicted that oxLDL has beneficial effects on some diseases, most of which were supported by evidence in the literature. Because DrugPattern predicted the potential beneficial effects of oxLDL in type 2 diabetes （T2D）, animal experiments were then performed to further verify this prediction. As a result, the experimental evidences validated the DrugPattern prediction that oxLDL indeed has beneficial effects on T2D in the case of energy restriction. These data confirmed the prediction accuracy of our approach and revealed unexpected protective roles for oxLDL in various diseases. This study provides a tool to infer patterns and rules in biomedical datasets based on drug set enrichment analysis.

关键词： Enrichment analysis Drug Data mining oxLDL Type 2 diabetes

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TISSUES 2.0: an integrative web resource on mammalian tissue expression (vol 2018, 2018)

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DATABASE-THE JOUrnaL OF BIOLOGICAL DATABASES AND CURATION 2018年第2018期2018卷 1-N.PAG页

作者： Palasca, Oana Santos, Alberto Stolte, Christian Gorodkin, Jan Jensen, Lars Juhl Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkCenter for non-coding RNA in Technology and Health Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkDepartment of Veterinary and Animal Sciences Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark New York Genome Center New York NY USA Center for non-coding RNA in Technology and Health Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkDepartment of Veterinary and Animal Sciences Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Correspondence may also be addressed to Jan Gorodkin. Email: gorodkin@rth.dk Novo Nordisk Foundation Center for Protein Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen DenmarkCenter for non-coding RNA in Technology and Health Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Corresponding author: Tel: +45 35325025 Email: lars.juhl.jensen@cpr.ku.dk

Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene-tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms *** URL: http://***/

关键词： DATABASES TRANSCRIPTOMES PROTEOMICS

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Proceedings of the EuBIC-MS 2020 Developers’ Meeting

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EuPA Open Proteomics 2020年 24卷 1-6页

作者： Christopher Ashwood Wout Bittremieux Eric W. Deutsch Nadezhda T. Doncheva Viktoria Dorfer Ralf Gabriels Vladimir Gorshkov Surya Gupta Andrew R. Jones Lukas Käll Dominik Kopczynski Lydie Lane Ludwig Lautenbacher Marc Legeay Marie Locard-Paulet Bart Mesuere Yasset Perez-Riverol Eugen Netz Sander Willems European Bioinformatics Community for Mass Spectrometry (info@***) Denmark Department of Cellular and Integrative Physiology University of Nebraska Medical Center Omaha USA Department of Computer Science University of Antwerp Antwerp Belgium Institute for Systems Biology Seattle WA 98109 USA Novo Nordisk Foundation Center for Protein Research University of Copenhagen Denmark Bioinformatics Research Group University of Applied Sciences Upper Austria Hagenberg Austria VIB-UGent Center for Medical Biotechnology VIB Ghent Belgium Department of Biochemistry and Molecular Biology University of Southern Denmark Denmark Institute of Systems Molecular and Integrative Biology University of Liverpool UK Science for Life Laboratory KTH - Royal Institute of Technology Solna Stockholm Sweden Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. Dortmund Germany SIB-Swiss Institute of Bioinformatics and Department of Microbiology and Molecular Medicine Faculty of Medicine Geneva University Geneva Switzerland Technical University of Munich Chair for Proteomics and Bioanalytics Freising Germany European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Wellcome Trust Genome Campus Hinxton Cambridge CB10 1SD UK Applied Bioinformatics Dept. of Computer Science University of Tübingen Tübingen Germany Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA 92093 USA Center for non-coding RNA in Technology and Health Department of Veterinary and Animal Sciences University of Copenhagen Denmark Department of Biomolecular Medicine Ghent University Ghent Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium Biomolecular Interactions Max Planck Institute for Developmental Biology Tübingen Germany

The 2020 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers’ meeting was held from January 13 th to January 17 th 2020 in Nyborg, Denmark. Among the participants were scientists as well as developers working in the field of computational mass spectrometry (MS) and proteomics. The 4-day program was split between introductory keynote lectures and parallel hackathon sessions. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts, and to actively contribute to highly relevant research projects. We successfully produced several new tools that will be useful to the proteomics community by improving data analysis as well as facilitating future research. All keynote recordings are available on https://***/10.5281/zenodo.3890181 .

关键词： Computational mass spectrometry Mass spectrometry Proteomics Bioinformatics Spectrum clustering Phosphoproteomics XIC extraction Proteomics graph networks Predicted spectra Metaproteomics Functional annotations Benchmark development

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Author Correction: A bioabsorbable mechanoelectric fiber as electrical stimulation suture

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Nature communications 2025年第1期16卷 898页

作者： Zhouquan Sun Yuefan Jin Jiabei Luo Linpeng Li Yue Ding Yu Luo Yan Qi Yaogang Li Qinghong Zhang Kerui Li Haibo Shi Shankai Yin Hongzhi Wang Hui Wang Chengyi Hou State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Shanghai P. R. China. Shanghai Key Laboratory of Sleep Disordered Breathing Department of Otolaryngology-Head and Neck Surgery Otolaryngology Institute of Shanghai JiaoTong University Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai P. R. China. Shanghai Key Laboratory of Sleep Disordered Breathing Department of Otolaryngology-Head and Neck Surgery Otolaryngology Institute of Shanghai JiaoTong University Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai P. R. China. lilp@***. Department of General Surgery Tongji Hospital Tongji University Medical School Shanghai P. R. China. Shanghai Engineering Research Center of Pharmaceutical Intelligent Equipment Shanghai Frontiers Science Research Center for Druggability of Cardiovascular Non-coding RNA Institute for Frontier Medical Technology School of Chemistry and Chemical Engineering Shanghai University of Engineering Science Shanghai P. R. China. Yangzhi Rehabilitation Hospital Affiliated to Tongji University Tongji University School of Medicine Shanghai P. R. China. State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Shanghai P. R. China. wanghz@***. Shanghai Key Laboratory of Sleep Disordered Breathing Department of Otolaryngology-Head and Neck Surgery Otolaryngology Institute of Shanghai JiaoTong University Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai P. R. China. wangh2005@alumni.***. State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Shanghai P. R. China. hcy@dhu.edu.cn.

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The Sierra Platinum Service for generating peak-calls for replicated ChIP-seq experiments

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BMC Research Notes 2018年第1期11卷 1-5页

作者： Wiegreffe, Daniel Müller, Lydia Steuck, Jens Zeckzer, Dirk Stadler, Peter F. Image and Signal Processing Group Department of Computer Science University of Leipzig Augustusplatz 10 Leipzig 04109 Germany Natural Language Processing Department Department of Computer Science University of Leipzig Augustusplatz 10 Leipzig 04109 Germany Bioinformatics Group Department of Computer Science University of Leipzig Härtelstraße 16-18 Leipzig 04107 Germany Interdisciplinary Center for Bioinformatics University of Leipzig Härtelstraße 16-18 Leipzig 04107 Germany Max Planck Institute MIS Inselstraße 22 Leipzig 04103 Germany Fraunhofer Institute for Cell Therapy and Immunology IZI Perlickstraße 1 Leipzig 04103 Germany Institute for Theoretical Chemistry University of Vienna Währinger Straße 17 Vienna 1090 Austria Center for Non-coding RNA in Technology and Health University of Copenhagen Grønnegårdsvej 3 Copenhagen 1870 Denmark Santa Fe Institute 1399 Hyde Park Road Santa Fe 87501 NM United States

Objective: Sierra Platinum is a fast and robust peak-caller for replicated ChIP-seq experiments with visual quality-control and -steering. The required computing resources are optimized but still may exceed the resources available to researchers at biological research institutes. Results: Sierra Platinum Service provides the full functionality of Sierra Platinum: using a web interface, a new instance of the service can be generated. Then experimental data is uploaded and the computation of the peaks is started. Upon completion, the results can be inspected interactively and then downloaded for further analysis, at which point the service terminates. © 2018 The Author(s).

关键词： ChIP-seq Histone modifications Peak-caller Replicate analysis

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