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Cryo-EM structure of human SRCAP complex

细胞研究（英文版） 2018年第11期28卷 1121-1123页

作者： Yangyang Feng Yuan Tian Zihan Wu Yanhui Xu Fudan University Shanghai Cancer Center Key Laboratory of Medical Epigenetics and Metabolism Institute of Biomedical Sciences Shanghai Medical College of Fudan University Shanghai 200032 China Fudan University Shanghai Cancer Center Key Laboratory of Medical Epigenetics and Metabolism Institute of Biomedical Sciences Shanghai Medical College of Fudan University Shanghai 200032 China Key Laboratory of Molecular Medicine Ministry of Education Department of Systems Biology for Medicine School of Basic Medical Sciences Shanghai Medical College of Fudan University Shanghai 200032 China State Key Laboratory of Genetic Engineering Collaborative Innovation Center of Genetics and Development School of Life Sciences Fudan University Shanghai 200433 China CAS Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Shanghai 200031 China

Dear Editor,Eukaryotic genome packs into highly condensed chromatin,in which genomic DNA wraps around histone octamer formed by evolutionarily conserved histone proteins H2A,H2B,H3,and *** histone variant H2A.Z primarily exists within nucleosomes that flank gene promoters,centromeres,and chromatin *** H2A.Z-containing nucleosomes undergo rapid turnover,which is important for the regulation of gene expression,DNA repair,and chromosome *** deposition of H2A.Z into genome is uniquely dependent on the SWI/SNF (switch/sucrose non-fermentable)-related Swr1 complex (referred to as Swr1-C hereafter) in yeast and SNF2-Related CBP Activator Protein (SRCAP) complex (referred to as SRCAP-C hereafter) in ***1-C/SRCAP-C incorporates H2A.Z/H2B dimer into canonical nucleosomes coupled with the eviction of H2A/H2B dimer in a stepwise exchange manner2-4.

关键词： Chromatin structure Cryoelectron microscopy

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Reversible hydrogels with tunable mechanical properties for optically controlling cell migration

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Nano Research 2018年第10期11卷 5556-5565页

作者： Xin Wu Wenmao Huang Wen-Hao Wu Bin Xue Dongfang Xiang Ying Li Meng Qin Fei Sun Wei Wang Wen-Bin Zhang Yi Cao Collaborative Innovation Center of Advanced Microstructures National Laboratory of Solid State Microstructure and Department of Physics Nanjing University Nanjing 210093 China Key Laboratory of Polymer Chemistry & Physics of Ministry of Education Center for Soft Matter Science and Engineering College ot Chemistry and Molecular Engineering Peking University Beijing 100871 China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University olin formation Science & Technology Nanjing 210044 China Department of Chemical and Biomolecular Engineering Division of BioMedical Engineering and Center for Systems Biology & Human Health The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong China

Synthetic hydrogels are widely used as biomimetic in vitro model systems to understand how cells respond to complex microenvironments. The mechanical properties of hydrogels are deterministic for many cellular behaviors, including cell migration, spreading, and differentiation. However, it remains a major challenge to engineer hydrogels that recapture the dynamic mechanical properties of native extracellular matrices. Here, we provide a new hydrogel platform with spatiotemporally tunable mechanical properties to assay and define cellular behaviors under light. The change in the mechanical properties of the hydrogel is effected by a photo-induced switch of the cross-linker fluorescent protein, Dronpa145N, between the tetrameric and monomeric states, which causes minimal changes to the chemical properties of the hydrogel. The mechanical properties can be rapidly and reversibly tuned for multiple cycles using visible light, as confirmed by rheological measurements and atomic force microscopy- based nano-indentation. We further demonstrated real-time and reversible modulation of cell migration behaviors on the hydrogels through photo-induced stiffness switching, with minimal invasion to the cultured cells. Hydrogels with a programmable mechanical history and a spatially defined mechanical hierarchy might serve as an ideal model system to better understand complex cellular functions.

关键词： Dronpa photo-responsive hydrogel mechanical properties cell migration artificial extracellular matrix

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Correction: A differential-targeting core-shell microneedle patch with coordinated and prolonged release of mangiferin and MSC-derived exosomes for scarless skin regeneration

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Materials horizons 2024年第11期11卷 2759页

作者： Shang Lyu Qi Liu Ho-Yin Yuen Huizhi Xie Yuhe Yang Kelvin Wai-Kwok Yeung Chak-Yin Tang Shuqi Wang Yaxiong Liu Bin Li Yong He Xin Zhao Department of Biomedical Engineering The Hong Kong Polytechnic University Hung Hom Hong Kong SAR 999077 China. Department of Applied Biology and Chemical Technology The Hong Kong Polytechnic University Hung Hom Hong Kong SAR 999077 China. xin.zhao@polyu.edu.hk. State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou Zhejiang 310027 China. yongqin@***. Department of Orthopaedics and Traumatology Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong SAR 999077 China. The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen Guangdong 518057 China. Department of Industrial & Systems Engineering The Hong Kong Polytechnic University Hung Hom Hong Kong SAR 999077 China. Tianfu Jincheng Laboratory City of Future Medicine Chengdu 641400 China. Clinical Research Center for Respiratory Disease West China Hospital Sichuan University Chengdu 610065 China. Jihua Laboratory Foshan Guangdong 528000 China. Medical 3D Printing Center Orthopedic Institute Department of Orthopaedic Surgery The First Affiliated Hospital School of Biology & Basic Medical Sciences Suzhou Medical College Soochow University Suzhou Jiangsu 215006 China. binli@***. Collaborative Innovation Center of Hematology Soochow University Suzhou Jiangsu 215006 China.

Correction for 'A differential-targeting core-shell microneedle patch with coordinated and prolonged release of mangiferin and MSC-derived exosomes for scarless skin regeneration' by Shang Lyu , , 2024, https:...

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Chinese guidelines for the application of colon cancer staging recognition systems based on artificial intelligence platforms (2021)

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Intelligent Medicine 2021年第1期1卷 37-42页

作者： Yun Lu Shuai Li Yuan Gao Yong Dai Bo Feng Fanghai Han Jiagang Han Jingjing He Xinxiang Li Guole Lin Qian Liu Guiying Wang Quan Wang Zhenning Wang Zheng Wang Aiwen Wu Bin Wu Yingchi Yang Hongwei Yao Wei Zhang Jianping Zhou Aimin Hao Zhongtao Zhang 无 Department of General Surgery The Affiliated Hospital of Qingdao UniversityQingdaoShandong 266003China Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing 100191China Department of General Surgery Qilu Hospital of Shandong UniversityJinanShandong 250012China Department of General Surgery Ruijin HospitalShanghai Jiao Tong University School of MedicineShanghai 200020China Shanghai Minimally Invasive Surgery Center Ruijin HospitalShanghai Jiao Tong University School of MedicineShanghai 200020China Department of Gastrointestinal Surgery Sun Yat-sen Memorial HospitalSun Yat-sen UniversityGuangzhouGuangdong 510120China Department of General Surgery Beijing Chaoyang HospitalCapital Medical UniversityBeijing 100027China Institute of International Law Chinese Academy of Social SciencesBeijing 102442China Department of Colorectal Surgery Fudan University Shanghai Cancer CenterShanghai 200032China Department of Oncology Shanghai Medical CollegeFudan UniversityShanghai 200032China Department of General Surgery Peking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Third Hospital of Hebei Medical University ShijiazhuangHebei 50051China Department of Colon and Rectum Surgery The First Hospital of Jilin UniversityChangchunJilin 130031China Department of Surgical Oncology and General Surgery Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal TumorsMinistry of EducationThe First Affiliated Hospital of China Medical UniversityShenyangLiaoning 110001China Department of Gastrointestinal Surgery Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei 430030China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education) Department of Unit II

The incidence and mortality of colon cancer in China are increasing each *** present,treatment selection for colon cancer patients mainly depends on imaging results,which require a large number of radiologists to *** China,there is a shortage and uneven distribution of experienced radiologists,which leads to delays and bias in the evaluation of imaging *** on these considerations,the Colorectal Surgery Group of the Surgery Branch of the Chinese Medical Association in collaboration with experts at Beihang University has independently developed an artificial intelligence(AI)-based recognition system for the preoperative determination of colon cancer stage to partially replace the work of and relieve the pressure on *** guidelines aim to standardize the use of AI-based recognition systems in the preoperative staging of colon cancer and guide their clinical application.

关键词： Artificial intelligence Colon cancer Deep learning Preoperative staging

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Breaking the symmetry: Gradient in NiFe layered double hydroxide nanoarrays for efficient oxygen evolution

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Nano Energy 2019年 60卷 661-666页

作者： Daojin Zhou Yin Jia Xinxuan Duan Jialun Tang Jie Xu Dong Liu Xuya Xiong Junming Zhang Jun Luo Lirong Zheng Bin Liu Yun Kuang Xiaoming Sun Xue Duan State Key Laboratory of Chemical Resource Engineering Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing University of Chemical Technology Beijing 100029 China School of Chemical and Biomedical Engineering Nanyang Technological University Singapore 637459 Singapore College of Energy Beijing University of Chemical Technology Beijing 100029 China Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems School of Materials Science & Engineering Beijing Institute of Technology 5 Zhongguancun South Street Haidian District Beijing 100081 China Center for Electron Microscopy TUT-FEI Joint Laboratory Tianjin Key Laboratory of Advanced Functional Porous Materials Institute for New Energy Materials & Low-Carbon Technologies School of Materials Science and Engineering Tianjin University of Technology Tianjin 300384 China Beijing Synchrotron Radiation Facility Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China

Breaking the symmetry in catalysts through interface engineering has emerged as a new dimension in enhancing the catalytic performances, while the long-range asymmetry (i.e. in nanometer scale) in catalysts can hardly be achieved by alloying or doping. Herein, we introduce asymmetrical gradient effect into NiFe layered double hydroxide (NiFe-LDH) at nano scale via a simple nanoarray construction strategy on Ni foam substrate. The electron energy loss spectroscopy, extended X-Ray absorption fine structure and other characterizations together revealed the concentration and valence states gradients in NiFe-LDH nanoarrays. Subsequently, the gradient effect leads to distinctly optimized binding strength of active sites to oxygen evolution intermediates, better electron transfers and boosted oxygen evolution performances, which are absent in non-gradient NiFe-LDH catalysts. Such long-range gradient effects in nanoarray materials provide new opportunities to understand their boosted catalytic performances and to rationally design better catalytic materials.

关键词： Layered double hydroxides Gradient materials Electron transfer Oxygen evolution

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医用增材制造——从前沿技术到产品研发

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engineering 2020年第11期6卷 31-41页

作者：邱贵兴丁文江田伟秦岭赵宇张联盟吕坚陈代杰袁广银吴成铁卢秉恒杜如虚陈继明 Mo Elbestawi 顾忠伟李涤尘孙伟赵远锦赫捷金大地刘斌张凯李鉴墨 Kam W.Leong 赵德伟郝定均敖英芳邓旭亮杨惠林徐少克陈英奇李龙樊建平聂国辉陈芸曾晖陈玮赖毓霄 Department of Orthopedics Peking Union Medical College Hospital Chinese Academy of Medical Science & Peking Union Medical College National Engineering Research Center of Light Alloys Net Forming & State Key Laboratory of Metal Matrix Composite Shanghai Jiao Tong University National Engineering Research Center of Mg Materials and Applications and School of Materials Science & Engineering Shanghai Jiao Tong University Department of Spine Surgery Beijing Jishuitan Hospital Center for Translational Medicine Research and Development Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Engineering Laboratory of Biomaterials Additive Manufacturing State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Center for Advanced Structural Materials City University of Hong Kong Shenzhen Research Institute Hong Kong Branch of National Precious Metals Material Engineering Research Center Department of Material Science and Engineering City University of Hong Kong Department of Mechanical Engineering City University of Hong Kong School of Pharmacy Shanghai Jiao Tong University China State Institute of Pharmaceutical Industry Shanghai Institute of Pharmaceutical Industry State Key Laboratory of High-Performance Ceramics and Superfine Microstructure Shanghai Institute of Ceramics Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering University of the Chinese Academy of Sciences Micro- and Nano-Technology Research Center State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University Shien-Ming Wu School of Intelligent Engineering Guangzhou International Campus South China University of Technology Beijing Engineering Research Center of 3D Printing for Digital Medical Health Beijing University of Technology Beijing Engineering Research Center of Laser Technology Beijing University of Technology Key Laboratory of Trans-Scale Las

1.医用增材制造原料的研发和挑战医用增材制造的原料与其他多个领域使用的原料具有广泛通用性,这是构成三维(3D)打印领域的重要基础。这些领域的增材制造在材料类型、粉体特性、成型性和黏弹性等方面面临着相同的问题和挑战。例如,航空...

1.医用增材制造原料的研发和挑战医用增材制造的原料与其他多个领域使用的原料具有广泛通用性,这是构成三维(3D)打印领域的重要基础。这些领域的增材制造在材料类型、粉体特性、成型性和黏弹性等方面面临着相同的问题和挑战。例如,航空领域采用了多种金属材料,而生物医学领域会使用金属、聚合物和无机材料。在生物医学领域,

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Reprogrammable 3D Mesostructures Through Compressive Buckling of Thin Films with Prestrained Shape Memory Polymer

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Acta Mechanica Solida Sinica 2018年第5期31卷 589-598页

作者： Xiaogang Guo Zheng Xu Fan Zhang Xueju Wang Yanyang Zi John A. Rogers Yonggang Huang Yihui Zhang Department of Engineering Mechanics Center for Mechanics and Materials and Center for Flexible Electronics Technology AML Tsinghua University Beijing 100084 China State Key Laboratory for Manufacturing and Systems Engineering School of Mechanical Engineering Xi'an Jiaotong University Xi'an 710049 China Simpson Querrey Institute and Feinberg Medical School Center for Bio-Integrated Electronics Northwestern University Evanston IL 60208 USA Departments of Materials Science and Engineering Biomedical Engineering Chemistry Mechanical Engineering Electrical Engineering and Computer Science and Neurological Surgery Center for Bio-Integrated Electronics Simpson Querrey Institute for Nano/biotechnology Northwestern University Evanston IL 60208 USA Departments of Civil and Environmental Engineering Mechanical Engineering and Materials Science and Engineering Center for Bio-Integrated Electronics Northwestern University Evanston IL 60208 USA

The mechanically guided assembly that relies on the compressive buckling of strate- gically patterned 2D thin films represents a robust route to complex 3D mesostructures in advanced materials and even functional micro-devices. Based on this approach, formation of complex 3D configurations with suspended curvy features or hierarchical geometries remains a challenge. In this paper, we incorporate the prestrained shape memory polymer in the 2D precur- sor design to enable local rolling deformations after the mechanical assembly through compressive buckling. A theoretical model captures quantitatively the effect of key design parameters on local rolling deformations. The combination of precisely controlled global buckling and local rolling expands substantially the range of accessible 3D configurations. The combined experimental and theoretical studies over a dozen of examples demonstrate the utility of the proposed strategy in achieving complex reprogrammable 3D mesostructures.

关键词： Mechanically guided 3D assembly Reprogrammable 3D mesostructures Shapememory polymer Buckling Rolling

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In vivo imaging using surface enhanced spatially offset raman spectroscopy (SESORS): balancing sampling frequency to improve overall image acquisition

Npj imaging

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Npj imaging 2024年第1期2卷 7-7页

作者： Fay Nicolson Bohdan Andreiuk Eunah Lee Bridget O'Donnell Andrew Whitley Nicole Riepl Deborah L Burkhart Amy Cameron Andrea Protti Scott Rudder Jiang Yang Samuel Mabbott Kevin M Haigis Department of Cancer Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA 02215 USA. Department of Imaging Dana-Farber Cancer Institute and Harvard Medical School Boston MA02215 USA. Cancer Immunology and Virology Dana-Farber Cancer Institute and Harvard Medical School Boston MA 02215 USA. HORIBA Instruments Incorporated Piscataway NJ 08854 USA. Honeywell International Inc. Fort Washington PA 19034 USA. College of Science Northeastern University 360 Huntington Avenue Boston MA 02115 USA. Innovative Photonic Solutions Monmouth Junction Plainsboro Township NJ 08852 USA. State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine Sun Yat-sen University Cancer Center Guangzhou China. Department of Biomedical Engineering Texas A&M University Emerging Technologies Building College Station TX 77840 USA. Center for Remote Health Technologies & Systems Texas A & M Engineering Experiment Station 600 Discovery Drive College Station TX 77840 USA.

In the field of optical imaging, the ability to image tumors at depth with high selectivity and specificity remains a challenge. Surface enhanced resonance Raman scattering (SERRS) nanoparticles (NPs) can be employed as image contrast agents to specifically target cells in vivo; however, this technique typically requires time-intensive point-by-point acquisition of Raman spectra. Here, we combine the use of "spatially offset Raman spectroscopy" (SORS) with that of SERRS in a technique known as "surface enhanced spatially offset resonance Raman spectroscopy" (SESORRS) to image deep-seated tumors in vivo. Additionally, by accounting for the laser spot size, we report an experimental approach for detecting both the bulk tumor, subsequent delineation of tumor margins at high speed, and the identification of a deeper secondary region of interest with fewer measurements than are typically applied. To enhance light collection efficiency, four modifications were made to a previously described custom-built SORS system. Specifically, the following parameters were increased: (i) the numerical aperture (NA) of the lens, from 0.2 to 0.34; (ii) the working distance of the probe, from 9 mm to 40 mm; (iii) the NA of the fiber, from 0.2 to 0.34; and (iv) the fiber diameter, from 100 μm to 400 μm. To calculate the sampling frequency, which refers to the number of data point spectra obtained for each image, we considered the laser spot size of the elliptical beam (6 × 4 mm). Using SERRS contrast agents, we performed in vivo SESORRS imaging on a GL261-Luc mouse model of glioblastoma at four distinct sampling frequencies: par-sampling frequency (12 data points collected), and over-frequency sampling by factors of 2 (35 data points collected), 5 (176 data points collected), and 10 (651 data points collected). In comparison to the previously reported SORS system, the modified SORS instrument showed a 300% improvement in signal-to-noise ratios (SNR). The results demonstrate the ability to

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MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

arXiv

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arXiv 2023年

作者： Li, Jianning Zhou, Zongwei Yang, Jiancheng Pepe, Antonio Gsaxner, Christina Luijten, Gijs Qu, Chongyu Zhang, Tiezheng Chen, Xiaoxi Li, Wenxuan Wodzinski, Marek Friedrich, Paul Xie, Kangxian Jin, Yuan Ambigapathy, Narmada Nasca, Enrico Solak, Naida Melito, Gian Marco Vu, Viet Duc Memon, Afaque R. Schlachta, Christopher De Ribaupierre, Sandrine Patel, Rajnikant Eagleson, Roy Chen, Xiaojun Mächler, Heinrich Kirschke, Jan Stefan de la Rosa, Ezequiel Christ, Patrick Ferdinand Li, Hongwei Bran Ellis, David G. Aizenberg, Michele R. Gatidis, Sergios Küstner, Thomas Shusharina, Nadya Heller, Nicholas Andrearczyk, Vincent Depeursinge, Adrien Hatt, Mathieu Sekuboyina, Anjany Löffler, Maximilian Liebl, Hans Dorent, Reuben Vercauteren, Tom Shapey, Jonathan Kujawa, Aaron Cornelissen, Stefan Langenhuizen, Patrick Ben-Hamadou, Achraf Rekik, Ahmed Pujades, Sergi Boyer, Edmond Bolelli, Federico Grana, Costantino Lumetti, Luca Salehi, Hamidreza Ma, Jun Zhang, Yao Gharleghi, Ramtin Beier, Susann Sowmya, Arcot Garza-Villarreal, Eduardo A. Balducci, Thania Angeles-Valdez, Diego Souza, Roberto Rittner, Leticia Frayne, Richard Ji, Yuanfeng Ferrari, Vincenzo Chatterjee, Soumick Dubost, Florian Schreiber, Stefanie Mattern, Hendrik Speck, Oliver Haehn, Daniel John, Christoph Nürnberger, Andreas Pedrosa, João Ferreira, Carlos Aresta, Guilherme Cunha, António Campilho, Aurélio Suter, Yannick Garcia, Jose Lalande, Alain Vandenbossche, Vicky Van Oevelen, Aline Duquesne, Kate Mekhzoum, Hamza Vandemeulebroucke, Jef Audenaert, Emmanuel Krebs, Claudia van Leeuwen, Timo Vereecke, Evie Heidemeyer, Hauke Röhrig, Rainer Hölzle, Frank Badeli, Vahid Krieger, Kathrin Gunzer, Matthias Chen, Jianxu van Meegdenburg, Timo Dada, Amin Balzer, Miriam Fragemann, Jana Jonske, Frederic Rempe, Moritz Malorodov, Stanislav Bahnsen, Fin H. Seibold, Constantin Jaus, Alexander Marinov, Zdravko Jaeger, Paul F. Stiefelhagen, Rainer Santos, Ana Sofia Lindo, Mariana Ferreira, André Alves, Victor Kamp, Michael Abourayya, Amr Nensa, Felix Hörst, Fabian Brehmer, Alexander Hein Girardetstraße 2 Essen45131 Germany Graz University of Technology Inffeldgasse 16c Graz8010 Austria Graz Austria The Department of Computer Science Johns Hopkins University Malone Hall 3400 N Charles St BaltimoreMD21218 United States Rte Cantonale Lausanne1015 Switzerland The Department of Measurement and Electronics AGH University of Science and Technology Krakow Poland Sierre Switzerland Department of Biomedical Engineering University of Basel Hegenheimermattweg Allschwil167C CH-4123 Switzerland The Boston College 140 Commonwealth Ave Chestnut HillMA02467 United States University Hospital B7-200 339 Windermere Road LondonN6A 5A5 Canada The Department of Radiology Renji Hospital School of Medicine Shanghai Jiao Tong University Shanghai200240 China The Research Center for Connected Healthcare Big Data ZhejiangLab Zhejiang Hangzhou311121 China The Faculty of Statistics Technical University Dortmund August-Schmidt-Straße 1 Dortmund44227 Germany The Institute of Mechanics Graz University of Technology Kopernikusgasse 24/IV Graz8010 Austria The Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China The Department of Cardiac Surgery Medical University Graz Auenbruggerplatz 29 Graz8036 Austria The Department of Diagnostic and Interventional Radiology University Hospital Giessen Justus-Liebig-University Giessen Klinikstraße 33 Giessen35392 Germany The Department of Mechanical Engineering Mehran University of Engineering and Technology Jamshoro Sindh76062 Pakistan The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China The Geschäftsführender Oberarzt Abteilung für Interventionelle und Diagnostische Neuroradiologie Universitätsklinikum der Technischen Universität München Ismaningerstr. 22 München81675 Germany icometrix Kolonel Be

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 datasets with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://***/ and https://***/Jianningli/*** Codes 68T01 © 2023, CC BY.

关键词： Large dataset

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Genomic evolution reshapes cell-type diversification in the amniote brain

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Developmental cell 2025年

作者： Duoyuan Chen Zhenkun Zhuang Maolin Huang Yunqi Huang Yuting Yan Yanru Zhang Youning Lin Xiaoying Jin Yuanmei Wang Jinfeng Huang Wenbo Xu Jingfang Pan Hong Wang Fubaoqian Huang Kuo Liao Mengnan Cheng Zhiyong Zhu Yinqi Bai Zhiwei Niu Ze Zhang Ya Xiang Xiaofeng Wei Tao Yang Tao Zeng Yuliang Dong Ying Lei Yangang Sun Jian Wang Huanming Yang Yidi Sun Gang Cao Muming Poo Longqi Liu Robert K Naumann Chun Xu Zhenlong Wang Xun Xu Shiping Liu BGI Research Hangzhou 310030 China BGI Research Shenzhen 518083 China Key Laboratory of Spatial Omics of Zhejiang Province BGI Research Hangzhou 310030 China State Key Laboratory of Genome and Multi-omics Technologies BGI Research Hangzhou 310030 China. School of Biology and Biological Engineering South China University of Technology Guangzhou 510006 China School of Life Sciences Zhengzhou University Zhengzhou 450001 China. BGI Research Hangzhou 310030 China. School of Biology and Biological Engineering South China University of Technology Guangzhou 510006 China. Key Laboratory of Spatial Omics of Zhejiang Province BGI Research Hangzhou 310030 China. College of Life Sciences University of Chinese Academy of Sciences Beijing 100049 China HIM-BGI Omics Center Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences Hangzhou 310018 China. The Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions Shenzhen 1068 Xueyuan Avenue Shenzhen University Town Nanshan District Shenzhen 518055 China. Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou 310024 China College of Life Sciences Northwest University Xi'an 710069 China. China National GeneBank BGI Research Shenzhen 518120 China Guangdong Genomics Data Center BGl research Shenzhen 518120 China. BGI Research Shenzhen 518083 China. Shanxi Medical University BGI Collaborative Center for Future Medicine Shanxi Medical University Taiyuan 030001 China. Institute of Neuroscience Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology CAS Center for Excellence in Brain Science and Intelligence Technology University of Chinese Academy of Sciences Chinese Academy of Sciences Shanghai 200031 China. HIM-BGI Omics Center

Over 320 million years of evolution, amniotes have developed complex brains and cognition through largely unexplored genetic and gene expression mechanisms. We created a comprehensive single-cell atlas of over 1.3 million cells from the telencephalon and cerebellum of turtles, zebra finches, pigeons, mice, and macaques, employing single-cell resolution spatial transcriptomics to validate gene expression patterns across species. Our study identifies significant species-specific variations in cell types, highlighting their conservation and diversification in evolution. We found pronounced differences in telencephalon excitatory neurons (EXs) and cerebellar cell types between birds and mammals. Birds predominantly express SLC17A6 in EX, whereas mammals express SLC17A7 in the neocortex and SLC17A6 elsewhere, possibly due to loss of function of SLC17A7 in birds. Additionally, we identified a bird-specific Purkinje cell subtype (SVIL+), implicating the lysine-specific demethylase 11 (LSD1)/KDM1A pathway in learning and circadian rhythms and containing numerous positively selected genes, which suggests an evolutionary optimization of cerebellar functions for ecological and behavioral adaptation. Our findings elucidate the complex interplay between genetic evolution and environmental adaptation, underscoring the role of genetic diversification in the development of specialized cell types across amniotes.

关键词： amniote brain science cerebellum evolution of cell types single-nucleus RNA-seq telencephalon

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