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Author Correction: Enhanced oxygen reduction with single-atomic-site iron catalysts for a zinc-air battery and hydrogen-air fuel cell

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Nature communications 2022年第1期13卷 921页

作者： Yuanjun Chen Shufang Ji Shu Zhao Wenxing Chen Juncai Dong Weng-Chon Cheong Rongan Shen Xiaodong Wen Lirong Zheng Alexandre I Rykov Shichang Cai Haolin Tang Zhongbin Zhuang Chen Chen Qing Peng Dingsheng Wang Yadong Li Department of Chemistry Tsinghua University 100084 Beijing China. Beijing Guyue New Materials Research Institute Beijing University of Technology 100124 Beijing China. Beijing Synchrotron Radiation Facility Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China. State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences 030001 Taiyuan China. Mössbauer Effect Data Center Dalian Institute of Chemical Physics Chinese Academy of Sciences 116023 Dalian China. State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology 430070 Wuhan China. State Key Lab of Organic-Inorganic Composites and Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing University of Chemical Technology 100029 Beijing China. Department of Chemistry Tsinghua University 100084 Beijing China. wangdingsheng@***.

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BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

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Nature methods 2023年第6期20卷 824-835页

作者： Linus Manubens-Gil Zhi Zhou Hanbo Chen Arvind Ramanathan Xiaoxiao Liu Yufeng Liu Alessandro Bria Todd Gillette Zongcai Ruan Jian Yang Miroslav Radojević Ting Zhao Li Cheng Lei Qu Siqi Liu Kristofer E Bouchard Lin Gu Weidong Cai Shuiwang Ji Badrinath Roysam Ching-Wei Wang Hongchuan Yu Amos Sironi Daniel Maxim Iascone Jie Zhou Erhan Bas Eduardo Conde-Sousa Paulo Aguiar Xiang Li Yujie Li Sumit Nanda Yuan Wang Leila Muresan Pascal Fua Bing Ye Hai-Yan He Jochen F Staiger Manuel Peter Daniel N Cox Michel Simonneau Marcel Oberlaender Gregory Jefferis Kei Ito Paloma Gonzalez-Bellido Jinhyun Kim Edwin Rubel Hollis T Cline Hongkui Zeng Aljoscha Nern Ann-Shyn Chiang Jianhua Yao Jane Roskams Rick Livesey Janine Stevens Tianming Liu Chinh Dang Yike Guo Ning Zhong Georgia Tourassi Sean Hill Michael Hawrylycz Christof Koch Erik Meijering Giorgio A Ascoli Hanchuan Peng Institute for Brain and Intelligence Southeast University Nanjing China. Microsoft Corporation Redmond WA USA. Tencent AI Lab Bellevue WA USA. Computing Environment and Life Sciences Directorate Argonne National Laboratory Lemont IL USA. Kaya Medical Seattle WA USA. University of Cassino and Southern Lazio Cassino Italy. Center for Neural Informatics Structures and Plasticity Krasnow Institute for Advanced Study George Mason University Fairfax VA USA. Faculty of Information Technology Beijing University of Technology Beijing China. Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing China. Nuctech Netherlands Rotterdam the Netherlands. Janelia Research Campus Howard Hughes Medical Institute Ashburn VA USA. Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada. Ministry of Education Key Laboratory of Intelligent Computation and Signal Processing Anhui University Hefei China. Paige AI New York NY USA. Scientific Data Division and Biological Systems and Engineering Division Lawrence Berkeley National Lab Berkeley CA USA. Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience UC Berkeley Berkeley CA USA. RIKEN AIP Tokyo Japan. Research Center for Advanced Science and Technology (RCAST) The University of Tokyo Tokyo Japan. School of Computer Science University of Sydney Sydney New South Wales Australia. Texas A&M University College Station TX USA. Cullen College of Engineering University of Houston Houston TX USA. Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan. National Centre for Computer Animation Bournemouth University Poole UK. PROPHESEE Paris France. Department of Neuroscience Columbia University New York NY USA. Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University New York NY USA. Department of Computer Science Northern Illinois Universit

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

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Flexible, ultrathin bioelectronic materials and devices for chronically stable neural interfaces

Brain‐X

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Brain‐X 2023年第4期1卷

作者： Lianjie Zhou Zhongyuan Wu Mubai Sun Jaejin Park Mengdi Han Ming Wang Junsheng Yu Zengfeng Di Yongfeng Mei Wubin Bai Xinge Yu Ki Jun Yu Enming Song Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai China Contribution: Investigation Visualization Writing - original draft Institute of Agro-food Technology Jilin Academy of Agricultural Sciences Changchun Jilin China Contribution: Data curation Investigation Functional Bio-integrated Electronics and Energy Management Lab School of Electrical and Electronic Engineering Yonsei University Seoul Korea Department of Biomedical Engineering College of Future Technology Peking University Beijing China Contribution: Resources Validation State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai China State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China (UESTC) Chengdu Sichuan China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Department of Material Science Fudan University Shanghai China Department of Applied Physical Sciences University of North Carolina at Chapel Hill Chapel Hill North Carolina USA Department of Biomedical Engineering City University of Hong Kong Hong Kong SAR China Wubin Bai Xinge Yu Ki Jun Yu and Enming Song. Contribution: Conceptualization Methodology Resources Supervision Writing - review & editing

Advanced technologies that can establish intimate, long-lived functional interfaces with neural systems have attracted increasing interest due to their wide-ranging applications in neuroscience, bioelectronic medicine, and the associated treatment of neurodegenerative diseases. A critical challenge of significance remains in the development of electronic platforms that offer conformal contact with soft brain tissue for the sensing or stimulation of brain activities and chronically stable operation in vivo, at scales that range from cellular-level resolution to macroscopic areas. This review summarizes recent advances in this field, with an emphasis on the use of demonstrated concepts, constituent materials, engineered designs, and system integration to address the current challenges. The article begins with an overview of recent bioelectronic platforms with unique form factors, ranging from filamentary probes to conformal sheets and three-dimensional frameworks for alleviating the mechanical mismatch between interface materials and neural tissues. Next, active interfaces which utilize inorganic/organic semiconductor-enabled devices are reviewed, highlighting various working principles of recording mechanisms including capacitively and conductively coupled sensing enabled by high transistor matrices at high spatiotemporal resolution. The subsequent section presents approaches to biological integration which use active materials for multiplexed addressing, local amplification and multimodal operation with high-channel-count and large-scale electronic systems in a safe fashion that provides multi-decade stable performance in both animal models and human subjects. The advances summarized in this review will guide the future direction of this technology and provide a basis for next-generation chronic neural interfaces with long-lived high-performance operation.

关键词： neural interface flexibility passive electrodes active recording barrier materials chronic stability

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Managing Multiple Halide-Related Defects for Efficient and Stable Inorganic Perovskite Solar Cells

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Angewandte Chemie 2023年第30期135卷

作者： Zhiteng Wang Prof. Qingwen Tian Hao Zhang Prof. Huidong Xie Yachao Du Lei Liu Xiaolong Feng Adel Najar Xiaodong Ren Prof. Shengzhong (Frank) Liu Key Laboratory of Applied Surface and Colloid Chemistry Ministry of Education Shaanxi Key Laboratory for Advanced Energy Devices Shaanxi Engineering Lab for Advanced Energy Technology School of Materials Science and Engineering Shaanxi Normal University Xi'an 710119 P. R. China Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Investigation (lead) Contribution: Conceptualization (lead) Funding acquisition (lead) Project administration (lead) Supervision (lead) Validation (lead) Writing - original draft (lead) Writing - review & editing (lead) Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049 P. R. China Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian 116023 P. R. China Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) School of Chemistry and Chemical Engineering Xi'an University of Architecture and Technology Xi'an 710055 P. R. China Contribution: Formal analysis (supporting) Validation (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Methodology (supporting) Resources (supporting) Department of Physics College of Science United Arab Emirates University Al Ain 15551 United Arab Emirates Contribution: Supervision (supporting) Validation (supporting) Writing - review & editing (supporting) Contribution: Data curation (supporting) Formal analysis (supporting) Methodology (supporting) Contribution: Funding acquisition (lead) Project administration (lead) Validation (lead) Writing - review & editing (lead)

Halide-related surface defects on inorganic halide perovskite not only induce charge recombination but also severely limit the long-term stability of perovskite solar cells. Herein, adopting density functional theory calculation, we verify that iodine interstitials (I i ) has a low formation energy similar to that of the iodine vacancy (V I ) and is also readily formed on the surface of all-inorganic perovskite, and it is regarded to function as an electron trap. We screen a specific 2,6-diaminopyridine (2,6-DAPy) passivator, which, with the aid of the combined effects from halogen-N pyridine and coordination bonds, not only successfully eliminates the I i and dissociative I 2 but also passivates the abundant V I . Furthermore, the two symmetric neighboring -NH 2 groups interact with adjacent halides of the octahedral cluster by forming hydrogen bonds, which further promotes the adsorption of 2,6-DAPy molecules onto the perovskite surface. Such synergetic effects can significantly passivate harmful iodine-related defects and undercoordinated Pb 2+ , prolong carrier lifetimes and facilitate the interfacial hole transfer. Consequently, these merits enhance the power-conversion efficiency (PCE) from 19.6 % to 21.8 %, the highest value for this type of solar cells, just as importantly, the 2,6-DAPy-treated CsPbI 3− x Br x films show better environmental stability.

关键词： All-Inorganic Perovskite CsPbI3−xBrx Defect Passivation Iodine-Related Defects Solar Cells

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Regulating the Mechanical and Optical Properties of Polymer-based Nanocomposites by Sub-Nanowires

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Angewandte Chemie 2022年第5期135卷

作者： Feng Yuan Dr. Chen Ouyang Minzheng Yang Prof. Wenxiong Shi Dr. Weibin Ren Prof. Yang Shen Prof. Yan Wei Prof. Xuliang Deng Prof. Xun Wang Institute of Medical Technology Peking University Health Science Center Beijing 100191 China Beijing Laboratory of Biomedical Materials Department of Geriatric Dentistry Peking University School and Hospital of Stomatology Beijing 100081 China Engineering Research Center of Advanced Rare Earth Materials Department of Chemistry Tsinghua University Beijing 100084 China Contribution: Data curation (lead) Formal analysis (lead) Investigation (lead) Writing - original draft (lead) Contribution: Data curation (supporting) Formal analysis (supporting) State Key Lab of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China Institute for New Energy Materials and Low Carbon Technologies School of Materials Science and Engineering Tianjin University of Technology Tianjin 300384 China Contribution: Software (supporting) Contribution: Formal analysis (supporting) Contribution: Formal analysis (supporting) Supervision (supporting) Contribution: Conceptualization (equal) Formal analysis (lead) Supervision (lead) Contribution: Conceptualization (lead) Supervision (lead) Contribution: Conceptualization (lead) Data curation (lead) Investigation (lead) Methodology (lead) Project administration (lead) Supervision (lead) Validation (lead) Writing - review & editing (lead)

Sub-nanowires (SNWs) exhibit great potential applications in nanocomposites owing to their high specific surface area, high flexibility, and similarity to polymer chains in dimension, which are a good entry point to bridge inorganic materials and polymer materials. Herein, we synthesized hydroxyapatite sub-nanowires (HAP SNWs) and engineered hydroxyapatite sub-nanowires/polyimide (HSP) gels and films by simple mixing of HAP SNWs and polyimide (PI). Benefiting from the interactions between HAP SNWs and PI, these nanocomposites were a continuous hybrid network. As the increase of HAP SNWs contents, the viscosity and modulus of HSP gels were greatly improved by one or two orders of magnitude compared with PI gel. HSP films not only maintained high transparency but also gained high haze, as well as exhibited enhanced Young's modulus. Thus, both HSP gels and films developed in this work are promising for various applications in coatings and high-performance films.

关键词： Gels Nanocomposites Nanowires Thin Films

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Supramolecular Engineering of Cathode Materials for Aqueous Zinc-ion Energy Storage Devices: Novel Benzothiadiazole Functionalized Two-Dimensional Olefin-Linked COFs

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Angewandte Chemie 2023年第10期135卷

作者： Dr. Haijun Peng Senhe Huang Dr. Verónica Montes-García Dr. Dawid Pakulski Dr. Haipeng Guo Dr. Fanny Richard Prof. Xiaodong Zhuang Prof. Paolo Samorì Dr. Artur Ciesielski Université de Strasbourg CNRS Institut de Science et d'Ingénierie Supramoléculaires 8 allée Gaspard Monge 67000 Strasbourg France Contribution: Data curation (lead) Investigation (lead) Writing - original draft (lead) Writing - review & editing (lead) The Soft2D Lab State Key Laboratory of Metal Matrix Composites Shanghai Key Laboratory of Electrical Insulation and Thermal Ageing School of Chemistry and Chemical Engineering Shanghai Jiao Tong University 200240 Shanghai China Centre for Advanced Technologies Adam Mickiewicz University Uniwersytetu Poznańskiego 10 61-614 Poznań Poland Adam Mickiewicz University Foundation Poznań Science and Technology Park Rubież 46 61-612 Poznań Poland

Two-dimensional covalent organic frameworks (COFs) have emerged as promising materials for energy storage applications exhibiting enhanced electrochemical performance. While most of the reported organic cathode materials for zinc-ion batteries use carbonyl groups as electrochemically-active sites, their high hydrophilicity in aqueous electrolytes represents a critical drawback. Herein, we report a novel and structurally robust olefin-linked COF-TMT-BT synthesized via the aldol condensation between 2,4,6-trimethyl-1,3,5-triazine (TMT) and 4,4′-(benzothiadiazole-4,7-diyl)dibenzaldehyde (BT), where benzothiadiazole units are explored as novel electrochemically-active groups. Our COF-TMT-BT exhibits an outstanding Zn 2+ storage capability, delivering a state-of-the-art capacity of 283.5 mAh g −1 at 0.1 A g −1 . Computational and experimental analyses reveal that the charge-storage mechanism in COF-TMT-BT electrodes is based on the supramolecularly engineered and reversible Zn 2+ coordination by the benzothiadiazole units.

关键词： Charge Storage Mechanism Covalent Organic Frameworks Energy Storage Devices Functional Porous Materials Zinc-Ion Batteries

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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Target-specificity of different amyrin subunits in impeding HCV influx mechanism inside the human cells considering the quantum tunnel profiles and molecular strings of the CD81 receptor: a combined in silico and in vivo study

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In silico pharmacology 2023年第1期11卷 8页

作者： Anika Jabin Mohammad Fahim Uddin Salauddin Al Azad Ashfaque Rahman Fawzia Tabassum Pritthy Sarker A K M Helal Morshed Samiur Rahman Fatima Fairuz Raisa Musfiqur Rahman Sakib Abeer Hasan Olive Tabassum Islam Ramisha Tahsin Shahlaa Zernaz Ahmed Partha Biswas Mst Umme Habiba Mahbuba Siddiquy Maryam Jafary Department of Biochemistry and Microbiology North South University Dhaka 1229 Bangladesh. College of Material Science and Engineering Zhejiang Sci-Tech University Hangzhou 310018 Zhejiang People's Republic of China. Key Laboratory of Industrial Biotechnology Ministry of Education School of Biotechnology Jiangnan University Wuxi 214122 Jiangsu Province People's Republic of China. Department of Genetic Engineering and Biotechnology Shahjalal University of Science and Technology Sylhet 3114 Bangladesh. Pathology and Pathophysiology Major Academy of Medical Science Zhengzhou University Zhengzhou City 450001 Henan Province People's Republic of China. Department of Electrical and Electronic Engineering Brac University Dhaka 1212 Bangladesh. Department of Pharmacy Bangabandhu Sheikh Mujibur Rahman Science and Technology University Gopalganj 8100 Bangladesh. Department of Pharmacy East West University Dhaka 1212 Bangladesh. Department of Computer Science and Engineering East West University Dhaka 1212 Bangladesh. Department of Pharmaceutical Sciences North South University Dhaka 1229 Bangladesh. Department of Genetic Engineering and Biotechnology Jashore University of Science and Technology Jashore 7408 Bangladesh. Data Science Research Unit RPG Interface Lab Jashore 7400 Bangladesh. State Key Laboratory of Food Science and Technology Jiangnan University Wuxi 214122 Jiangsu Province People's Republic of China. Division of Food Safety and Hygiene Department of Environmental Health Engineering School of Public Health Tehran University of Medical Sciences Tehran *** Iran.

HCV is a hepatotropic RNA virus recognized for its frequent virulence and fatality worldwide. Despite many vaccine development programs underway, researchers are on a quest for natural bioactive compounds due to their multivalent efficiencies against viral infections, considering which the current research aimed to figure out the target-specificity and therapeutic potentiality of α, β, and δ subunits of amyrin, as novel bioactive components against the HCV influx mechanism. Initially, the novelty of amyrin subunits was conducted from 203 pharmacophores, comparing their in-silico pharmacokinetic and pharmacodynamic profiles. Besides, the best active site of CD81 was determined following the quantum tunneling algorithm. The molecular dynamic simulation was conducted (100 ns) following the molecular docking steps to reveal the parameters- RMSD (Å); Cα; RMSF (Å); MolSA (Å); Rg (nm); PSA (Å); SASA (Å), and the MM-GBSA dG binding scores. Besides, molecular strings of CD81, along with the co-expressed genes, were classified, as responsible for encoding CD81-mediated protein clusters during HCV infection, resulting in the potentiality of amyrins as targeted prophylactics in HCV infection. Finally, in vivo profiling of the oxidative stress marker, liver-specific enzymes, and antioxidant markers was conducted in the DMN-induced mice model, where -amyrin scored the most significant values in all aspects.

关键词： CD81 receptor Co-expressed genes behind HCV invasion DMN-induced hepatic fibrosis HCV infection In-silico pharmacokinetics and pharmacodynamics Target-specificity of amyrins

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Circularly and Linearly Polarized Luminescence from AIE Luminogens Induced by Super-Aligned Assemblies of Sub-1 nm Nanowires

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Angewandte Chemie 2022年第34期134卷

作者： Shujian Rong Prof. Wenxiong Shi Dr. Simin Zhang Prof. Dr. Xun Wang Key Lab of Organic Optoelectronics and Molecular Engineering Department of Chemistry Tsinghua University Beijing 100084 China Contribution: Investigation (lead) Methodology (lead) Writing - original draft (lead) Institute for New Energy Materials and Low Carbon Technologies School of Materials Science and Engineering Tianjin University of Technology Tianjin 300387 China Contribution: Data curation (lead) Formal analysis (lead) Software (lead) Contribution: Conceptualization (equal) Formal analysis (lead) Methodology (lead) Writing - review & editing (equal) Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Funding acquisition (lead) Investigation (lead) Methodology (lead) Project administration (lead) Resources (lead) Supervision (lead) Validation (lead) Writing - review & editing (lead)

Sub-1 nm nanowires (SNWs) combine the properties of inorganic materials and polymers. They can be highly oriented through assembly, and can also be easily processed. Meanwhile, aggregation-induced emission luminogens (AIEgens) show high potential for optical applications, but they are usually hard to process. The combination of SNWs and AIEgens can enrich both of their applications. In this study, we report that the fluorescence emission intensity of the AIEgens–SNW dispersion is dramatically enhanced due to the flexibility of SNWs. Furthermore, we fabricate two kinds of functional films with circularly polarized luminescence (CPL) and linearly polarized luminescence (LPL) activities. The construction of CPL materials didn't require any chiral chemicals. The construction of LPL materials didn't require an additional stretching process. As a result, we endowed common achiral AIEgens with a high dissymmetry factor of 0.033 and a polarization ratio of 0.44, respectively.

关键词： Aggregation-Induced Emission (AIE) Circularly Polarized Luminescence Linearly Polarized Luminescence Self-Assembly Sub-1 nm Nanowires

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Tracing the accretion history of supermassive Black Holes through X-ray variability: Results from the Chandra Deep Field-South

arXiv

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arXiv 2017年

作者： Paolillo, M. Papadakis, I. Brandt, W.N. Luo, B. Xue, Y.Q. Tozzi, P. Shemmer, O. Allevato, V. Bauer, F.E. Comastri, A. Gilli, R. Koekemoer, A.M. Liu, T. Vignali, C. Vito, F. Yang, G. Wang, J.X. Zheng, X.C. Dipartimento di Fisica "Ettore Pancini" Università di Napoli Federico II via Cintia 80126 Italy INFN Unità di Napoli via Cintia 9 Napoli80126 Italy Agenzia Spaziale Italiana Science Data Center Via del Politecnico snc Roma00133 Italy Physics Department University of Crete Heraklion Crete710 03 Greece Foundation for Research and Technology - Hellas IESL Voutes Heraklion Crete71110 Greece Department of Astronomy & Astrophysics 525 Davey Lab Pennsylvania State University University ParkPA16802 United States Institute for Gravitation and the Cosmos Pennsylvania State University University ParkPA16802 United States School of Astronomy and Space Science Nanjing University Nanjing210093 China CAS Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Hefei Anhui230026 China INAF Osservatorio Astrofisico di Firenze Largo Enrico Fermi 5 FirenzeI-50125 Italy Department of Physics University of North Texas DentonTX76203 United States Department of Physics University of Helsinki Gustaf Hällströmin katu 2a HelsinkiFI-00014 Finland University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Instituto de Astrofísica and Centro de Astroingeniería Facultad de Física Pontificia Universidad Católica de Chile Casilla 306 Santiago 22 Chile INAF Osservatorio Astronomico di Bologna via Gobetti 93/3 Bologna40129 Italy Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Dipartimento di Fisica e Astronomia Università degli Studi di Bologna via Gobetti 93/2 Bologna40129 Italy Astronomy Department University of Massachusetts AmherstMA01003 United States Casilla 306 Santiago Chile Space Science Institute 4750 Walnut Street Suite 205 BoulderCO80301 United States

We study the X-ray variability properties of distant AGNs in the Chandra Deep Field-South region over 17 years, up to z ∼ 4, and compare them with those predicted by models based on local samples. We use the results of Monte Carlo simulations to account for the biases introduced by the discontinuous sampling and the low-count regime. We confirm that variability is an ubiquitous property of AGNs, with no clear dependence on the density of the environment. The variability properties of high-z AGNs, over different temporal timescales, are most consistent with a Power Spectral Density (PSD) described by a broken (or bending) power-law, similar to nearby AGNs. We confirm the presence of an anti-correlation between luminosity and variability, resulting from the dependence of variability on BH mass and accretion rate. We explore different models, finding that our acceptable solutions predict that BH mass influences the value of the PSD break frequency, while the Eddington ratio λEdd affects the PSD break frequency and, possibly, the PSD amplitude as well. We derive the evolution of the average λEdd as a function of redshift, finding results in agreement with measurements based on different estimators. The large statistical uncertainties make our results consistent with a constant Eddington ratio, although one of our models suggest a possible increase of λEdd with lookback time up to z ∼ 2 − 3. We conclude that variability is a viable mean to trace the accretion history of supermassive BHs, whose usefulness will increase with future, wide-field/large effective area X-ray missions. Copyright © 2017, The Authors. All rights reserved.

关键词： Galaxies

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