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Diagnosis and Treatment Guidelines for Mesenchymal Stem Cell Therapy for Coronavirus Disease 2019(Beijing,2021)

Infectious Diseases & Immunity 2021年第2期1卷 68-73页

作者： Ruonan Xu Lei Shi Wei-Fen Xie Zhe Xu Fan-Ping Meng Jun-Liang Fu Xin Yuan Lei Huang Ming Shi Yonggang Li Yuanyuan Li Chen Yao Yu Zhang Zhongmin Liu Chenyan Gao Zhaohui Wu Shufang Meng Weidong Han Charlie Xiang Gui-Qiang Wang Taisheng Li Xiaoying Wang Yunxia Sun Zunyou Wu Wenhong Zhang Chunhua Zhao Yu Hu Tao Cheng Yuquan Wei Qi Zhou Fu-Sheng Wang Department of Infectious Diseases Fifth Medical Center of Chinese PLA General HospitalNational Clinical Research Center for Infectious DiseasesBeijing 100039China Department of Gastroenterology Changzheng Hospital of the Second Military Medical UniversityShanghai 200001China Department of Medical Statistics Peking University First HospitalBeijing 100191China National Industrial Base for Stem Cell Engineering Products Tianjin 300384China Department of Cardiac Surgery Shanghai East HospitalTongji UniversityShanghai 310000China Office of Clinical Evaluation of Biological Products Center for Drug EvaluationChina Food and Drug AdministrationBeijing 100053China China Medicinal Biotech Association Beijing 100022China National Cell Collection and Research Center Institute for Biological Product ControlNational Institutes for Food and Drug ControlTiantanXiliDongcheng DistrictBeijing 100050China State Key Laboratory for Diagnosis and Treatment of Infectious Diseases National Clinical Research Center for Infectious DiseasesCollaborative Innovation Center for Diagnosis and Treatment of Infectious Diseasesthe First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhou 310003China Department of Infectious Diseases and the Center for Liver Diseases Peking University First HospitalBeijing 100034China Department of Infectious Diseases Peking Union Medical College HospitalPeking Union Medical CollegeChinese Academy of Medical SciencesBeijing 100730China Radiology Department Peking University First HospitalBeijing 100034China JOINN Laboratories(Beijing) Beijing 100176China Chinese Center for Disease Control and Prevention Beijing 102206China Department of Infectious Diseases Huashan HospitalShanghai Medical CollegeFudan UniversityShanghai 200040China CAS Key Laboratory of Microbial Physiological and Metabolic Engineering State Key Laboratory of Microbial ResourcesInstitute of MicrobiologyChinese Academy of SciencesBeijing 100730China Union Hospital Tongji Medical CollegeHuazh

The coronavirus disease 2019(COVID-19)can be caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection,and has led to millions of deaths among more than 100 million infected people around the world according to the declaration from World Health *** immune response of both the innate and adaptive immune systems is subsistent on COVID-19 patients,of which the degree are associated with disease severity,lung damage and long term functional *** treatment options have included antiretroviral drugs,anti-inflammatory factors,antibodies,immune checkpoint inhibitors,and convalescent plasma *** recently,mesenchymal stem cell(MSC)therapy has been explored for the management and control of COVID-19,particularly with the aim of preventing or at least mitigating respiratory *** the safety and efficacy of stem cell therapy have been validated in multiple phase I–III clinical trials,to date,no standardized stem cell preparation,administration dosage or interval,product QA/QC testing,storage,transportation,or disposal protocols have been *** present paper proposes a systematic methodology that addresses all the foregoing process steps and evaluation criteria for the efficacious and safe administration of MSCs in the treatment of patients infected with COVID-19.

关键词： COVID-19 Mesenchymal stem cell Treatment

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Compensation effects of coated cysteamine on meat quality, amino acid composition, fatty acid composition, mineral content in dorsal muscle and serum biochemical indices in finishing pigs offered reduced trace minerals diet

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Science China(Life Sciences) 2019年第11期62卷 1550-1553页

作者： Miaomiao Bai Hongnan Liu Kang Xu Xiaofeng Zhang Baichuan Deng Chengquan Tan Jinping Deng Pingping Bing Yulong Yin National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production Hunan Province Key Laboratory of Animal Nutritional Physiology and Metabolic ProcessHunan Provincial Engineering Research Center of Healthy LivestockKey Laboratory of Agro-ecological Processes in Subtropical RegionInstitute of Subtropical AgricultureChinese Academy of SciencesChangsha 410125China College of Animal Science South China Agricultural UniversityGuangzhou 510642China Hunan Co-Innovation Center of Animal Production Safety Changsha 410128China Hangzhou King Techina Technology Company Academician Expert Workstation Hangzhou King Techina Technology Co.Ltd.Hangzhou 311107China Academics Working Station Changsha Medical UniversityChangsha 410219China

Dear *** mineral elements(ME)and amino acids have been demonstrated to be essential bioelements in animal *** there is a deficiency in ME,a number of biological functions in animals may be affected,including physical growth,psychomotor development,and *** of pig diets with ME is known to improve the animals'growth,reproduction,and their immunity against oxidative stress and cell damage.

关键词： indices oxidative finishing

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A network flow based energy-efficient backhauling algorithm for mm-wave small cell networks

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Journal of Computers (Taiwan) 2019年第6期30卷 155-167页

作者： Guo, Qun Wang, Xing-Gui Yang, Wei-Man Ma, Zhong-Yu College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou730050 China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou730050 China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology Lanzhou730050 China Department of Electronic Information Engineering Lanzhou Institute of Technology Lanzhou730050 China

The millimeter wave small cell backhaul network is one of the key solutions in 5G small cell backhaul. However, a lot of new challenges will be faced the multi-hop path planning is designed. In this paper, a flow network based energy efficient backhaul path planning algorithm (FBPA) is proposed for highly dense millimeter wave small cell networks so that the backhaul path planning with maximum throughput as well as minimum energy consumption is obtained. Firstly, the backhaul path planning problem is modelled as an integer programming (IP) problem, which is always a NP-hard problem. Then, a liner relaxation technique is used to make the problem be easier to resolve. Finally, the FBPA algorithm is proposed to find the path planning with minimum cost and maximum flow. Extensive simulations are conducted, the simulation results show that the backhaul throughput is improved by about 66.7% and energy efficiency is decreased by nearly 10% when the FBPA is compared to the existing path planning algorithm. © 2019 Computer Society of the Republic of China. All rights reserved.

关键词： Motion planning

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Advances in energy efficiency for carbon emissions neutrality

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Energy 2025年 328卷

作者： Chew Tin Lee Bohong Wang Jeng Shiun Lim Yee Van Fan Sin Yong Teng Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia 81310 Johor Bahru Johor Malaysia National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology/Zhejiang Key Laboratory of Pollution Control for Port-Petrochemical Industry Zhejiang Ocean University No. 1 Haida South Road Zhoushan 316022 China Environmental Change Institute (ECI) School of Geography and the Environment University of Oxford Oxford OX13QY United Kingdom Sustainable Process Integration Laboratory – SPIL NETME Centre Faculty of Mechanical Engineering Brno University of Technology - VUT Brno Technická 2896/2 616 69 Brno Czech Republic Department of Circular Chemical Engineering Faculty of Science and Engineering Maastricht University Urmonderbaan 22 6162 Geleen the Netherlands

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Multi-model Dynamic Fusion Soft-sensing Modeling and Its Application 36

Multi-model Dynamic Fusion Soft-sensing Modeling and Its App...

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第36届中国控制会议

作者： Chunyan Lu Wei Li Chaoqun Zhu Lanzhou University of Technology Gansu Province Key Laboratory of Industrial Process Advanced Control

ISBN: (纸本)9781538629185

In this paper,a multi-model dynamic fusion soft sensor modeling method based on Gauss-Markov estimation is ***,the fuzzy c-means algorithm is used to cluster the input samples of the *** radial basis function and least square support vector machine are used to establish multiple sub-models for each *** multi-model outputs are predicted by dynamic fusing the values of sub-models based on the Gauss-Markov *** proposed method is applied to predict alumina powder flow in the process of alumina *** results indicate that the proposed method has higher predictive accuracy and better generalization capability in comparison with the other soft sensor methods.

关键词： Soft sensor Fuzzy c-means clustering Radial basis function Least square support vector machine Gauss-Markov estimation

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The forefront of chemical engineering research

Nature Chemical Engineering

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Nature Chemical Engineering 2024年第1期1卷 18-27页

作者： Laura Torrente-Murciano Jennifer B. Dunn Panagiotis D. Christofides Jay D. Keasling Sharon C. Glotzer Sang Yup Lee Kevin M. Van Geem Jean Tom Gaohong He Department of Chemical Engineering and Biotechnology University of Cambridge Cambridge UK Chemical and Biological Engineering Center for Engineering Sustainability and Resilience Northwestern University Evanston IL USA Department of Chemical and Biomolecular Engineering University of California Los Angeles Los Angeles CA USA Department of Chemical & Biomolecular Engineering University of California Berkeley Berkeley CA USA Department of Bioengineering University of California Berkeley Berkeley CA USA California Institute of Quantitative Biosciences (QB3) University of California Berkeley Berkeley CA USA Division of Biological Systems and Engineering Lawrence Berkeley National Laboratory Berkeley CA USA Joint BioEnergy Institute Emeryville CA USA Center for Biosustainability Danish Technical University Lyngby Denmark Center for Synthetic Biochemistry Shenzhen Institutes for Advanced Technologies Shenzhen China Department of Chemical Engineering University of Michigan Ann Arbor MI USA Metabolic and Biomolecular Engineering National Research Laboratory Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory Department of Chemical and Biomolecular Engineering (BK21 four) BioProcess Engineering Research Center Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Laboratory for Chemical Technology Department of Materials Textiles and Chemical Engineering Faculty of Engineering and Architecture Ghent University Ghent Belgium Chemical Process Development Global Product Development and Supply Bristol Myers Squibb New Brunswick NJ USA State Key Laboratory of Fine Chemicals R&D Center of Membrane Science and Technology School of Chemical Engineering Panjin Institute of Industrial Technology Liaoning Key Laboratory of Chemical Additive Synthesis and Separation Dalian University of Technology Dalian Liaoning China

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Corrigendum to <'The evolution of carbon footprint in the yangtze river delta city cluster during economic transition 2012–2015′>

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Resources, Conservation and Recycling 2022年 184卷

作者： Chengqi Xia Heran Zheng Jing Meng Shuping Li Pengfei Du Yuli Shan State Key Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing 100084 China Industrial Ecology Programme Department of Energy and Process Engineering Norwegian University of Science and Technology Trondheim 7491 Norway The Bartlett School of Sustainable Construction University College London London WC1H0QB UK Institute of Blue and Green Development Shandong University Weihai 264209 China Integrated Research for Energy Environment and Society (IREES) Energy and Sustainability Research Institute Groningen University of Groningen Groningen the Netherlands

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A re-evaluation of the Chaetothyriales using criteria of comparative biology

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Fungal Diversity 2020年第4期103卷 47-85页

作者： Yu Quan Lucia Muggia Leandro F.Moreno Meizhu Wang Abdullah M.S.Al-Hatmi Nickolas da Silva Menezes Dongmei Shi Shuwen Deng Sarah Ahmed Kevin D.Hyde Vania A.Vicente Yingqian Kang JBenjamin Stielow Sybren de Hoog Centre of Expertise in Mycology of Radboud University Medical Centre/Canisius Wilhelmina Hospital NijmegenThe Netherlands Key Laboratory of Environmental Pollution Monitoring and Disease Control Ministry of Education of Guizhou&Key Laboratory of Medical Microbiology and ParasitologySchool of Basic Medical SciencesGuizhou Medical UniversityGuiyangChina College of Food and Pharmaceutical Engineering Guizhou Institute of TechnologyGuiyangChina Department of Life Sciences University of TriesteTriesteItaly Amsterdam Medical Center AmsterdamThe Netherlands Foundation Atlas of Clinical Fungi HilversumThe Netherlands Ministry of Health Directorate General of Health ServicesIbriOman Postgraduate Program in Microbiology Parasitology and PathologyBiological SciencesDepartment of Basic PathologyFederal University of ParanaCuritibaBrazil Department of Dermatology&Laboratory of Medical Mycology Jining No.1 People’s HospitalJiningShandongChina Department of Medical Microbiology People’s Hospital of Suzhou National New&Hi-Tech Industrial Development ZoneSuzhouChina Center of Excellence in Fungal Diversity Mae Fah Luang UniversityChiang RaiThailand Thermo Fisher Diagnostics Specialty Diagnostics GroupLandsmeerThe Netherlands Guizhou Academy of Tobacco Science GuiyangChina Engineering Bioprocess and Biotechnology Post-graduation Program Department of Bioprocess Engineering and BiotechnologyFederal University of ParanaCuritibaBrazil

Chaetothyriales is an ascomycetous order within *** order is particularly known through the black yeasts and filamentous relatives that cause opportunistic infections in *** species in the order are consistently *** and habitats of species are highly diverse,and often rather extreme in terms of exposition and *** are defined on the basis of evolutionary history,which is reconstructed by time of divergence and concepts of comparative biology using stochastical character mapping and a multi-rate Brownian motion model to reconstruct ecological ancestral character *** is hypothesized to be with a rock-inhabiting life *** disparity increased significantly in late Jurassic,probably due to expansion of cytochromes followed by colonization of vacant *** diversification took place subsequently,but at a low level of innovation resulting in strong niche conservatism for extant *** are ecologically different in degrees of *** of the clades has adapted ant domatia,which are rich in *** derived families,similar processes have enabled survival in domesticated environments rich in creosote and toxic hydrocarbons,and this ability might also explain the pronounced infectious ability of vertebrate hosts observed in these *** systems of morphological classification poorly correspond with recent phylogenetic *** are hypothesized to have low competitive ability against neighboring microbes,which interferes with their laboratory isolation on routine *** dataset is unbalanced in that a large part of the extant biodiversity has not been analyzed by molecular methods,novel taxonomic entities being introduced at a regular *** study comprises all available species sequenced to date for LSU and ITS,and a nomenclatural overview is provided.A limited number of species could not be assigned to any extant family.

关键词： Black yeasts Phylogeny Ecology Ancestral reconstruction Evolution Nomenclature

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A Novel Scalable Semi-supervised GMM and Its Application for Multimode process Quality Prediction with Big Data

A Novel Scalable Semi-supervised GMM and Its Application for...

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Data Driven control and Learning Systems (DDCLS)

作者： Le Yao Zhiqiang Ge Weiming Shao Zhihuan Song State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control College of Control Science and Engineering Zhejiang University Hangzhou P. R. China

ISBN: (纸本)9781538626191

In this paper, a novel variational inference semi-supervised GMM (VI-S 2 GMM) model is firstly proposed for multimode process predictive modeling with semi-supervised data. Since all the labeled and unlabeled data samples are involved in each iteration of parameter updating, an intractable computing problem occurs when facing a high-dimension and large-scale dataset. To tack this problem, a scalable Stochastic Variational Inference semi-supervised GMM (SVI-S 2 GMM) is further proposed for massive semi-supervised data. Through taking advantage of stochastic gradient optimization algorithm to maximize the Evidence of Lower Bound (ELBO), the VI-based algorithm becomes scalable. In SVI-S 2 GMM, only one or a mini-batch of samples is randomly selected to update parameters in each iteration, which is more efficient than VI-S 2 GMM. In this way, a large number of unlabeled process data can be useful in the modeling, which will benefit the parameter identification. The SVI-S 2 GMM is then exploited for the prediction of quality-related key performance index (KPI). Two modeling cases with large scale of semi-supervised datasets demonstrate the feasibility and effectiveness of the proposed algorithms.

关键词： Data models Inference algorithms Big Data Predictive models Adaptation models Computational modeling Stochastic processes

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Culture versus Policy: More Global Collaboration to Effectively Combat COVID-19

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The Innovation 2020年第2期1卷 15-16页

作者： Jianping Li Kun Guo Enrique Herrera Viedma Heesoek Lee Jiming Liu Ning Zhong Luiz Flavio Autran Monteiro Gomes Florin Gheorghe Filip Shu-Cherng Fang Mujgan SagirÖzdemir Xiaohui Liu Guoqing Lu Yong Shi School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100190China Research Center on Fictitious Economy&Data Science Chinese Academy of SciencesBeijing 100190China Department of Computer Science and Artificial Intelligence E.T.S.de Ingenieria Informatica y de TelecomunicacionesUniversity of Granada18071 GranadaSpain Department of Information Management Korea Advanced Institute of Science and TechnologySeoul 207-43 Korea Department of Computer Science and HKBU-CSD&NIPD Joint Research Laboratory for Intelligent Disease Surveillance and Control Hong Kong Baptist UniversityHong KongChina Department of Life Science and Informatics Maebashi Institute of TechnologyMaebashi 371-0816Japan Ibmec University Center Av.Presidente Wilson118Office#111020030-020 Rio de JaneiroBrazil The Romanian Academy Bucharest010071Romania Industrial and Systems Engineering Department North Carolina State UniversityRaleighNC 27695USA Department of Industrial Engineering Eskisehir Osmangazi University26480 EskisehirTurkey Department of Computer Science Brunel University LondonLondonUB83PHUK Department of Biology and School of Interdisciplinary Informatics University of Nebraska at OmahaOmahaNE 68182USA College of Information Science and Technology University of Nebraska at OmahaOmahaNE 68182USA

The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic *** and anti-epidemic policy do not necessarily conflict with each *** countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcome this historically tragic pandemic together.

关键词： seeking overcome policy

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