检索结果-内蒙古大学图书馆

arXiv 2024年

作者： LaBella, Dominic Baid, Ujjwal Khanna, Omaditya McBurney-Lin, Shan McLean, Ryan Nedelec, Pierre Rashid, Arif Tahon, Nourel Hoda Altes, Talissa Bhalerao, Radhika Dhemesh, Yaseen Godfrey, Devon Hilal, Fathi Floyd, Scott Janas, Anastasia Kazerooni, Anahita Fathi Kirkpatrick, John Kent, Collin Kofler, Florian Leu, Kevin Maleki, Nazanin Menze, Bjoern Pajot, Maxence Reitman, Zachary J. Rudie, Jeffrey D. Saluja, Rachit Velichko, Yury Wang, Chunhao Warman, Pranav Adewole, Maruf Albrecht, Jake Anazodo, Udunna Anwar, Syed Muhammad Bergquist, Timothy Chen, Sully Francis Chung, Verena Conte, Gian-Marco Dako, Farouk Eddy, James Ezhov, Ivan Khalili, Nastaran Iglesias, Juan Eugenio Jiang, Zhifan Johanson, Elaine Van Leemput, Koen Li, Hongwei Bran Linguraru, Marius George Liu, Xinyang Mahtabfar, Aria Meier, Zeke Moawad, Ahmed W. Mongan, John Piraud, Marie Shinohara, Russell Takeshi Wiggins, Walter F. Abayazeed, Aly H. Akinola, Rachel Jakab, András Bilello, Michel de Verdier, Maria Correia Crivellaro, Priscila Davatzikos, Christos Farahani, Keyvan Freymann, John Hess, Christopher Huang, Raymond Lohmann, Philipp Moassefi, Mana Pease, Matthew W. Vollmuth, Phillipp Sollmann, Nico Diffley, David Nandolia, Khanak K. Warren, Daniel I. Hussain, Ali Fehringer, Pascal Bronstein, Yulia Deptula, Lisa Stein, Evan G. Taherzadeh, Mahsa de Oliveira, Eduardo Portela Haughey, Aoife Kontzialis, Marinos Saba, Luca Turner, Benjamin Brüßeler, Melanie M.T. Ansari, Shehbaz Gkampenis, Athanasios Weiss, David Maximilian Mansour, Aya Shawali, Islam H. Yordanov, Nikolay Stein, Joel M. Hourani, Roula Moshebah, Mohammed Yahya Abouelatta, Ahmed Magdy Rizvi, Tanvir Willms, Klara Martin, Dann C. Okar, Abdullah D'Anna, Gennaro Taha, Ahmed Sharifi, Yasaman Faghani, Shahriar Kite, Dominic Pinho, Marco Haider, Muhammad Ammar Aristizabal, Alejandro Karargyris, Alexandros Kassem, Hasan Pati, Sarthak Sheller, Micah Alonso-Basanta, Michelle Villanueva-Meyer, Javier Rauschecker, Andreas M. Nada, Ayman Aboian, Mariam Flanders, Adam E. Wiestler, Benedikt Bakas, Spyridon Ca Duke University Medical Center Department of Radiation Oncology DurhamNC United States Division of Computational Pathology Department of Pathology Laboratory Medicine Indiana University School of Medicine IndianapolisIN United States Center for Federated Learning in Medicine Indiana University IndianapolisIN United States Department of Neurosurgery Thomas Jefferson University PhiladelphiaPA United States University of California San FranciscoCA United States Yale University New HavenCT United States Department of Radiation Oncology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States University of Missouri ColumbiaMO United States Department of Biostatistics and Health Data Science Indiana University School of Medicine IndianapolisIN United States Children's Hospital of Philadelphia University of Pennsylvania PhiladelphiaPA United States University of Pennsylvania PhiladelphiaPA United States Helmholtz AI Helmholtz Munich Germany Department of Informatics Technical University Munich Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Germany San FranciscoCA United States Biomedical Image Analysis and Machine Learning Department of Quantitative Biomedicine University of Zurich Switzerland Department of Neuroradiology Technical University of Munich Munich Germany University of San Diego CA United States Cornell University IthacaNY United States Department of Radiology Northwestern University EvanstonIL United States Duke University Medical Center School of Medicine DurhamNC United States Lab Crestview Radiology Lagos Nigeria Sage Bionetworks United States McGill University MontrealQC Canada Children's National Hospital WashingtonDC United States George Washington University WashingtonDC United State

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, T2/FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps. © 2024, CC BY.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

From FAIR to CURE: Guidelines for Computational Models of Biological Systems

arXiv

引用

arXiv 2025年

作者： Sauro, Herbert M. Agmon, Eran Blinov, Michael L. Gennari, John H. Hellerstein, Joe Heydarabadipour, Adel Hunter, Peter Jardine, Bartholomew E. May, Elebeoba Nickerson, David P. Smith, Lucian P. Bader, Gary D. Bergmann, Frank Boyle, Patrick M. Dräger, Andreas Faeder, James R. Feng, Song Freire, Juliana Fröhlich, Fabian Glazier, James A. Gorochowski, Thomas E. Helikar, Tomas Hoops, Stefan Imoukhuede, Princess Keating, Sarah M. Konig, Matthias Laubenbacher, Reinhard Loew, Leslie M. Lopez, Carlos F. Lytton, William W. McCulloch, Andrew Mendes, Pedro Myers, Chris J. Myers, Jerry G. Mulugeta, Lealem Niarakis, Anna van Niekerk, David D. Olivier, Brett G. Patrie, Alexander A. Quardokus, Ellen M. Radde, Nicole Rohwer, Johann M. Sahle, Sven Schaff, James C. Sego, T.J. Shin, Janis Snoep, Jacky L. Vadigepalli, Rajanikanth Wiley, H. Steve Waltemath, Dagmar Moraru, Ion Department of Bioengineering University of Washington SeattleWA98195-5061 United States Intelligent Systems Engineering and Biocomplexity Institute Indiana University Street BloomingtonIN47408 United States Center for Cardiovascular Biology University of Washington SeattleWA98195-5061 United States eScience Institute University of Washington SeattleWA98195-5061 United States Institute for Stem Cell and Regenerative Medicine University of Washington SeattleWA98195-5061 United States School of Biological Sciences University of Bristol 24 Tyndall Avenue BristolBS8 1TQ United Kingdom Departments of Physiology & Pharmacology Neurology Downstate Health Science University BrooklynNY11203 United States Department of Neurology Kings County Hospital BrooklynNY11203 United States NASA-John H. Glenn Research Center MS 110-3 21000 Brookpark Road ClevelandOH44135 United States Center for Cell Analysis and Modeling UConn Health 263 Farmington Avenue FarmingtonCT06030-6406 United States Amsterdam Institute for Life and Environment Vrije Universiteit Amsterdam De Boelelaan 1108 Amsterdam1081 HZ Netherlands Department of Pathology and Genomic Medicine Thomas Jefferson University 1020 Locust St PhiladelphiaPA19107 United States Biological Sciences Division Pacific Northwest National Laboratory 902 Battelle Blvd RichlandWA99354 United States Auckland Bioengineering Institute University of Auckland Auckland1010 New Zealand Center of Integrative Biology University of Toulouse III-Paul Sabatier 165 Rue Marianne Grunberg-Manago Toulouse31400 France Lifeware Group Inria Building Alan Turing 1 Rue Honoré d’Estienne d’Orves Palaiseau91120 France Multiscale Modeling Group Altos Labs Redwood CityCA94065 United States partner site Tübingen Tübingen Germany Ottfried-Müller-Str. 37 Tübingen72076 Germany 06120 Germany Department of Computer Science Center for Data Science New York University New YorkNY11201 United States Department of Bi

Guidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility;the clarity of model descriptions and annotations for understandability;adherence to standards and open science practices for reproducibility;and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible. © 2025, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Global Riverine Export of Dissolved Lignin Constrained by Hydrology, Geomorphology, and Land-Cover

引用

Global Biogeochemical Cycles 2023年第4期37卷 e2022GB007607-e2022GB007607页

作者： Hongyan Bao Ying Wu Xiaoqian Zhan Xiaona Wang Robert G. M. Spencer Peter J. Hernes Xiaojuan Feng Li-Chin Lee Jr-Chuan Huang Jingjing Zhang Hongwei Zhao Shuh-Ji Kao Jing Zhang State Key Laboratory of Marine Environmental Science College of Ocean and Earth Sciences Xiamen University Xiamen China H. Bao and Y. Wu Contribution: Conceptualization Formal analysis Data curation Writing - original draft Writing - review & editing Funding acquisition State Key Laboratory of Estuarine and Coastal Research East China Normal University Shanghai China Contribution: Conceptualization Writing - review & editing Funding acquisition Contribution: Data curation Visualization Contribution: Data curation Department of Earth Ocean and Atmospheric Science Florida State University Tallahassee FL USA Contribution: Writing - review & editing Department of Land Air and Water Resources University of California Davis CA USA State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences Beijing China Department of Geography National Taiwan University Taipei Taiwan State Key Laboratory of Marine Resource Utilization in South China Sea Hainan University Haikou China Center for Eco-Environment Restoration of Hainan Province College of Environment and Ecology Hainan University Haikou China Contribution: Writing - review & editing Funding acquisition Contribution: Conceptualization Writing - review & editing

The land-to-ocean export of terrestrial dissolved organic matter (tDOM) links the two largest organic carbon (OC) pools on Earth and is changing due to anthropogenic activity and climate change. Lignin phenols are often utilized as diagnostic markers for tDOM in aquatic systems, but information on the global dissolved lignin flux is still uncertain as linkages between future changes in export and global changes are poorly constrained. Thirty-two new measurements from 15 Chinese rivers and 548 measurements collected from 97 global rivers were combined to analyze its distributions, fluxes, and potential controls. Dissolved lignin concentrations (in μg L−1) varied by more than two orders of magnitude (0.7–138 μg L−1) and were positively correlated with dissolved OC (DOC) concentrations globally, suggesting coupled export of dissolved lignin and DOC. The carbon-normalized lignin yields (in mg g OC−1) varied by an order of magnitude (<1–30 mg (g OC)−1) and was significantly lower in the Arctic than in temperate and tropical rivers. Correlation analyses indicated that the dissolved lignin flux (FLignin) was mainly affected by water discharge and mean basin slope, while the area-normalized yield of dissolved lignin as well as discharge-weighted lignin concentration strongly and positively correlated with forest coverage. We, for the first time, estimated global FLignin ranges from 0.58 to 1.2 Tg yr−1 by using different approaches. Our synthesis reveals that future changes in land-cover that is driven by climate change as well as other human activities would impose a significant influence on the land-to-ocean export of tDOM.

关键词： dissolved lignin land-cover global flux terrestrial organic matter

来源：评论

学校读者我要写书评

暂无评论

Target localization intervention and prognosis evaluation for an individual with mild cognitive impairment

Brain‐X

引用

Brain‐X 2023年第3期1卷

作者： Weiping Wang Haiyan Zhao Chang He Yuanbo Cui Zhen Wang Alexander Hramov Ping Luan Xiong Luo Jipeng Ouyang Kurths Jürgen School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan Guangdong China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Contribution: Writing - review & editing Department of Neurology Peking University Third Hospital Beijing China Contribution: Resources Zhen Wang The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi 710072 China. Contribution: Writing - original draft The 6th Research Institute of China Electronics Corporation Beijing China The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi China Chang He School of Computer and Communication Engineering University of Science and Technology Beijing Beijing 100083 China. Contribution: Investigation Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Saratov State Medical University Saratov Russia Contribution: Data curation Guangdong Second Provincial General Hospital & Health Science Center Shenzhen Guangdong China Department of Neurology Shunde Hospital Southern Medical University Foshan Guangdong China Institute of Physics Humboldt-University Berlin Germany Potsdam Institute for Climate Impact Research Potsdam Germany

Currently, no specific treatments are available for Alzheimer's disease (AD). Mild cognitive impairment (MCI), the preclinical stage of AD, has a high possibility of reversing symptoms through neural regulation. A state dynamics model for single brain regions was developed to simulate blood oxygen level-dependent signals in a patient with early mild cognitive impairment. Subsequently, the analysis of functional connections was used to comprehensively consider multiple complex network centralities to locate the intervention targets, and a multiple brain region collaborative control scheme was designed. Finally, the reliability and effectiveness of the intervention were verified at the brain region and subnetwork levels. This technique provides a basis for future clinical diagnosis and treatment of AD and MCI.

关键词： adaptive pinning control Alzheimer's disease BOLD signals computational modeling Sub_network

来源：评论

学校读者我要写书评

暂无评论

computer-Aided Discovery of Potent Broad-Spectrum Vaccine Adjuvants

引用

Angewandte Chemie 2023年第18期135卷

作者： Juan Ma Shenqing Wang Chuanfang Zhao Xiliang Yan Quanzhong Ren Zheng Dong Jiahuang Qiu Yin Liu Qing'e Shan Ming Xu Bing Yan Sijin Liu State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 P. R. China School of Environmental Sciences University of Chinese Academy of Sciences Beijing 100049 P. R. China Contribution: Data curation (lead) Formal analysis (lead) Funding acquisition (supporting) Investigation (lead) Methodology (equal) Visualization (equal) Writing - original draft (lead) Institute of Environmental Research at Greater Bays Key Laboratory for Water Quality and Conservation of the Pearl River Delta Ministry of Education Guangzhou University Guangzhou 510006 P. R. China Contribution: Conceptualization (equal) Data curation (equal) Formal analysis (supporting) Investigation (supporting) Methodology (lead) School of Chemical Sciences University of Chinese Academy of Sciences Beijing 100049 P. R. China Contribution: Methodology (supporting) Software (lead) Visualization (lead) Contribution: Methodology (supporting) Software (lead) Visualization (supporting) Department of toxicology and sanitary chemistry School of public health Capital Medical University Beijing 100069 P. R. China Contribution: Data curation (supporting) Investigation (supporting) School of Environment Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou 330106 P. R. China Contribution: Formal analysis (supporting) Methodology (supporting) Medical Science and Technology Innovation Center Shandong First Medical University & Shandong Academy of Medical Sciences Jinan Shandong 250117 P. R. China Contribution: Investigation (supporting) Contribution: Supervision (supporting) Contribution: Conceptualization (equal) Funding acquisition (supporting) Methodology (supporting) Project administration (equal) Writing - review & editing (equal) Contribution: Conceptualization (equal) Funding acquisition (lead) Project administration (lead) Supervision (lead) Writing - review & editing (lead)

Adjuvants stimulate the immune system to vigorously respond to a vaccine. While current adjuvants such as aluminum salts and oil-in-water emulsions have been used for decades, they do not generate broad and long-lasting responses in many vaccines. Consequently, more potent adjuvants are needed. Here, using computer-aided molecule design and machine learning, we discovered 2 new, broad-spectrum adjuvants that can boost vaccine responses. Our library containing 46 toll-like receptor (TLR)-targeting agonist ligands were assembled on Au nanoparticles. Comprehensive in vitro , ex vivo and in vivo studies showed both leads promoted dendritic cell activation via multiple TLRs and enhanced antigen presentation to T cells. When used together with tumor-specific antigens to immunize mice against B16-OVA melanoma and 4T1-PD1 breast cancer, both adjuvants unleashed strong immune responses that suppressed tumor growth and lung metastases. Our results show computer-aided design and screening can rapidly uncover potent adjuvants for tackling waning immunity in current vaccines.

关键词： Cancer Immunotherapy computer-Aided Design Dendritic Cell Nano Adjuvant Pattern Recognition Receptor

来源：评论

学校读者我要写书评

暂无评论

The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

引用

NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

来源：评论

学校读者我要写书评

暂无评论

Inferring the population history of Kyrgyz in Xinjiang, Northwest China from genome-wide array genotyping

引用

American Journal of Biological Anthropology 2023年第4期181卷

作者： Bubibatima Halili Xiaomin Yang Rui Wang Kongyang Zhu Xiangjun Hai Chuan-Chao Wang Department of Anthropology and Ethnology Institute of Anthropology School of Sociology and Anthropology Xiamen University Xiamen China Contribution: Conceptualization (equal) Resources (lead) Xiangjun Hai State Key Laboratory of Cellular Stress Biology School of Life Sciences Xiamen University Xiamen 361102 China. Contribution: Conceptualization (equal) Data curation (lead) Formal analysis (lead) Visualization (lead) Writing - original draft (lead) State Key Laboratory of Cellular Stress Biology School of Life Sciences Xiamen University Xiamen China Contribution: Data curation (equal) Formal analysis (equal) Key Laboratory of Environmental Ecology and Population Health in Northwest Minority Areas Northwest Minzu University Lanzhou China Xiaomin Yang and Chuan-Chao Wang Department of Anthropology and Ethnology Institute of Anthropology School of Sociology and Anthropology Xiamen University 361005 Xiamen China. Contribution: Conceptualization (equal) Resources (equal) State Key Laboratory of Marine Environmental Science Xiamen University Xiamen China Institute of Artificial Intelligence Xiamen University Xiamen China Ministry of Education Key Laboratory of Contemporary Anthropology Department of Anthropology and Human Genetics School of Life Sciences Fudan University Shanghai China Contribution: Conceptualization (lead) Project administration (lead) Supervision (lead) Writing - review & editing (lead)

Objectives Xinjiang plays a vital role in the trans-Eurasian population migration, language diffusion, and culture and technology exchange. However, the underrepresentation of Xinjiang's genomes has hindered a more comprehensive understanding of Xinjiang's genetic structure and population history. Materials and Methods We collected and genotyped 70 southern Xinjiang's Kyrgyz (SXJK) individuals and combined the data with modern and ancient Eurasians published. We used allele-frequency methods, including PCA, ADMIXTURE, f -statistics, qpWave/qpAdm , ALDER, Treemix, and haplotype-shared methods including shared-IBD segments, fineSTRUCTURE, and GLOBETROTTER to unveil the fine-scale population structure and reconstruct admixture history. Results We identified genetic substructure within the SXJK population with subgroups showing different genetic affinities to West and East Eurasians. All SXJK subgroups were suggested to have close genetic relationships with surrounding Turkic-speaking groups that is, Uyghur, Kyrgyz from north Xinjiang and Tajikistan, and Chinese Kazakh, suggesting a shared ancestry among those populations. Outgroup- f 3 and symmetrical f 4 statistics showed a high genetic affinity of SXJK to present-day Tungusic, Mongolic-speaking populations and Ancient Northeast Asian (ANA) related groups. Allele sharing and haplotype sharing profiles revealed the east–west admixture pattern of SXJK. The qpAdm -based admixture models showed that SXJK derived ancestry from East Eurasian (ANA and East Asian, 42.7%–83.3%) and West Eurasian (Western Steppe herders and Central Asian, 16.7%–57.3%), the recent east–west admixture event could be traced to 1000 years ago based on ALDER and GLOBETROTTER analysis. Discussion The high genetic affinity of SXJK to present-day Tungusic and Mongolic-speaking populations and short-shared IBD segments indicated their shared common ancestry. SXJK harbored a close genetic affinity to ANA-related populations, indicating the Northeast Asia

关键词： admixture history genetic continuity genetic structure genome-wide SNP Kyrgyz

来源：评论

学校读者我要写书评

暂无评论

The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

引用

NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

来源：评论

学校读者我要写书评

暂无评论

Living cell-laden hydrogels: Unleashing the future of responsive biohybrid systems

Responsive Materials

引用

Responsive Materials 2023年第1期1卷

作者： Xuejia Hu Bing Lei Sen-Sen Li Lu-Jian Chen Quan Li Department of Electronic Engineering School of Electronic Science and Engineering Fujian Key Laboratory of Ultrafast Laser Technology and Applications Xiamen University Xiamen China Contribution: Conceptualization (equal) Data curation (equal) Funding acquisition (supporting) Writing - original draft (lead) Writing - review & editing (lead) Contribution: Formal analysis (supporting) Visualization (equal) Writing - original draft (equal) Writing - review & editing (equal) Contribution: Funding acquisition (supporting) Visualization (supporting) Writing - original draft (supporting) Writing - review & editing (supporting) Contribution: Conceptualization (equal) Funding acquisition (lead) Project administration (equal) Resources (lead) Writing - original draft (equal) Writing - review & editing (equal) Institute of Advanced Materials and School of Chemistry and Chemical Engineering Southeast University Nanjing China Lu-Jian Chen and Quan Li. Contribution: Conceptualization (equal) Validation (supporting) Writing - original draft (supporting) Writing - review & editing (supporting)

Responsive biohybrid systems have the potential to overcome limitations of both natural and artificial machines in terms of efficiency, accuracy, and functionality. As functional units, living cells act as bricks for building biohybrid machines, where the extracellular matrix mimics hydrogels to act as ideal biological concrete. Combining living cells with hydrogels offers unique advantages in simulating human tissues or organs, which unleashes the future of biohybrid systems, and thus has attracted extensive attention. Herein, recent progress in cell-laden hydrogel-based responsive biohybrid systems is summarized to provide a basic understanding of how these systems are built from the bottom up and how to achieve the complex functions. This review focuses on advanced manufacturing technologies for responsive biohybrid systems, including laden cells in hydrogel matrices, three-dimensional bioprinting, and microfluidic manufacturing. Subsequently, the innovative applications of these works, including actuators, sensors, and engineered functional materials, are presented, along with different triggering mechanisms that are highlighted. Finally, the current challenges and future opportunities in the field are addressed. This review provides a unique perspective and is hoped to inspire fields such as biohybrid technologies, soft robots, and tissue engineering.

关键词： hydrogel living cell responsive biohybrid system soft robot

来源：评论

学校读者我要写书评

暂无评论

Search for the doubly heavy baryons Ω^(0)_(bc) and E^(0)_(bc) decaying to Λ^(+)_(c)π^(-) and E^(+)_(c)π^(-)

引用

Chinese Physics C 2021年第9期45卷 10-21页

作者： R.Aaij C.Abelian Beteta T.Ackernley B.Adeva M.Adinolfi H.Afshamia C.A.Aidala S.Aiola Z.Ajaltouni S.Aka J.Albrecht F.Alessio M.Alexander A.Alfonso Albero Z.Aliouche G.Alkhazov P.Alvarez Cartelie S.Amato Y.Amhis L.An L.Anderlini A.Andreianov M.Andreotti F.Archilli A.Artamonov M.Artuso K.Arzymatov E.Aslanides M.Atzeni B.Audurier S.Bachmann M.Bachmayer J.J.Back P.Baladron Rodriguez V.Balagura W.Baldini J.Baptista Leite R.J.Barlow S.Barsuk W.Barter M.Bartolini F.Baryshnikov J.M.Basels G.Bassi B.Batsukh A.Battig A.Bay M.Becker F.Bedeschi I.Bediaga A.Beiter V.Belavin S.Belin V.Bellee K.Belous I.Belov I.Belyaev G.Bencivenni E.Ben-Haim A.Berezhnoy *** D.Beminghoff H.C.Bernstein C.Bertella A.Bertolin C.Betancourt F.Betti Ia.Bezshyiko S.Bhasin J.Bhom L.Bian M.S.Bieker S.Bifani P.Billoir M.Birch F.C.R.Bishop A.Bitadze A.Bizzeti M.Bjorn M.P.Blago T.Blake F.Blanc S.Blusk D.Bobulska J.A.Boelhauve O.Boente Garcia T.Boettcher A.Boldyrev A.Bondar N.Bondar S.Borghi M.Borisyak M.Borsato J.T.Borsuk S.A.Bouchiba T.J.V.Bowcock A.Boyer C.Bozzi M J.Bradley S.Braun A.Brea Rodriguez M.Brodski J.Brodzicka A.Brossa Gonzalo D.Brundu A.Buonaura C.Burr A.Bursche A.Butkevich J.S.Butter J.Buytaert W.Byczynski S.Cadeddu H.Cai R.Calabrese L.Calefice L.Calero Diaz S.Cali R.Calladine M.Calvi M.Calvo Gomez P.Camargo Magalhaes A.Camboni P.Campana A.F.Campoverde Quezada S.Capelli L.Capriotti A.Carbone G.Carboni R.Cardinale A.Cardini I.Carli P.Camiti L.Carus K.Carvalho Akiba A.Casais Vidal G.Casse M.Cattaneo G.Cavallero S.Celani J.Cerasoli A.J.Chadwick M.G.Chapman M.Charles Ph.Charpentier G.Chatzikonstantinidis C.A.Chavez Barajas M.Chefdeville C.Chen S.Chen A.Chernov V.Chobanova S.Cholak M.Chrzaszcz A.Chubykin V.Chulikov P.Ciambrone M.F.Cicala X.Cid Vidal G.Ciezarek P.E.L.Clarke M.Clemencic H.V.Cliff J.Closier J.L.Cobbledick V.Coco J.A.B.Coelho J.Cogan E.Cogneras L.Cojocariu P.Collins T.Colombo L.Congedo A.Contu N.Cooke G.Coombs G.Corti C.M.Costa Sobral B.Couturier D.C.Craik J.Crkovska M.Cruz Torres R.Currie C.L.Da Silva E.Dall'Occo J.Dalseno C.D'Ambrosi Centro Brasileiro de Pesquisas Fisicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina Institute of High Energy Physics(IHEP) BeijingChina School of Physics State Key Laboratory of Nuclear Physics and Technology Peking UniversityBeijingChina University ofChinese Academy of Sciences BeijingChina Institute of Particle Physics Central China Normal UniversityWuhanHubeiChina Univ.Savoie Mont Blanc CNRSIN2P3-LAPPAnnecyFrance Universite Clermont Auvergne CNRS/IN2P3LPCClermont-FerrandFrance Aix Marseille Univ CNRS/IN2P3CPPMMarseilleFrance Universite Paris-Saclay CNRS/IN2P3IJCLabOrsayFrance Laboratoire Leprince-Ringuet CNRS/IN2P3Ecole PolytechniqueInstitut Polytechnique de ParisPalaiseauFrance LPNHE Sorbonne UniversiteParis Diderot Sorbonne Paris CiteCNRS/FN2P3ParisFrance I.Physikalisches Institut RWTH Aachen UniversityAachenGermany Fakultat Physik Technische Universitat DortmundDortmundGermany Max-Planck-Institut für Kemphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universitat HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland INFN Sezione di Bari BariItaly INFN Sezione di Bologna BolognaItaly INFN Sezione di Ferrara FerraraItaly INFN Sezione di Firenze FirenzeItaly INFN Laboratori Nazionali di Frascati FrascatiItaly INFN Sezione di Genova GenovaItaly INFN Sezione di Milano MilanoItaly INFN Sezione di Milano-Bicocca MilanoItaly INFN Sezione di Cagliari MonserratoItaly Universita degli Studi di Padova Universita e INFNPadovaPadovaItaly INFN Sezione di Pisa PisaItaly INFN Sezione di Roma La Sapienza RomaItaly INFN Sezione di Roma Tor Vergata RomaItaly Nikhef National Institute for Subatomic Physics AmsterdamNetherlands Nikhef National Institute for Subatomic Physics and VU University Amsterdam AmsterdamNetherlands AGH-University of Science and Technology Faculty of Physics and Applied Computer ScienceKr

The first search for the doubly heavyΩ^(0)_(bc)baryon and a search for the E^(0)_(bc)baryon are performed using pp collision data collected via the LHCb experiment from 2016 to 2018 at a centre-of-mass energy of 13 TeV,corresponding to an integrated luminosity of 5.2 fb^(-1).The baryons are reconstructed via their decays to Λ^(+)_(c)π^(-)and E^(+)_(c)π^(-).No significant excess is fbund for invariant masses between 6700 and 7300 MeV/c^(2),in a rapidity range from 2.0 to 4.5 and a transverse momentum range from 2 to 20 MeV/*** limits are set on the ratio of the Ω^(0)_(bc)and E^(0)_(bc)production cross-section times the branching fraction to Λ^(+)_(c)π^(-)(E^(+)_(c)π^(-))relative to that of the Λ^(0)_(b)(E^(0)_(b))baryon,for different lifetime hypotheses,at 95%confidence *** upper limits range from 0.5 x 10^(-4)to 2.5 x 10^(-4)for theΩ^(0)_(bc)→Λ^(+)_(c)π^(-)(E^(0)_(bc)→Λ^(+)_(c)π^(-))decay,and from 1.4x 10^(-3)to 6.9 x 10^(-3)for theΩ^(0)_(bc)→E^(+)_(c)π^(-)(E^(0)_(bc)→E^(+)_(c)π^(-))decay,depending on the considered mass and lifetime of theΩ^(0)_(bc)(E^(0)_(bc))baryon.

关键词： B physics quarkonium spectroscopy heavy quark production

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：