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A cellular hierarchy in melanoma uncouples growth and metastasis

四川生理科学杂志 2022年第9期44卷 1633-1633页

作者： Panagiotis Karras Laboratory for Molecular Cancer Biology Center for Cancer Biology VIB Leuven Belgium Department of Oncology KU Leuven Leuven Belgium Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK The Wellcome Trust/CRUK Gurdon Institute University of Cambridge Cambridge UK Department of General Medical Oncology UZ Leuven Leuven Belgium BGI-Shenzhen Shenzhen China VIB BioImaging Core VIB Center for Brain and Disease Research Leuven Belgium VIB Bioimaging Core VIB Center for Inflammation Research Ghent Belgium Department of Biomedical Molecular Biology Ghent University Ghent Belgium FACS Expertise Center Center for Cancer Biology VIB Leuven Belgium Laboratory of Tumor Microenvironment and Therapeutic Resistance Center for Cancer Biology VIB Leuven Belgium Center for Brain & Disease Research VIB-KU Leuven Leuven Belgium Department of Human Genetics KU Leuven Leuven Belgium Data Mining and Modeling for Biomedicine Group VIB Center for Inflammation Research Ghent Belgium Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium Laboratory for Translational Cell and Tissue Research Department of Imaging and Pathology KU Leuven Leuven Belgium Laboratory of Translational Genetics Center for Cancer Biology VIB Leuven Belgium Laboratory of Translational Genetics Center for Human Genetics KU Leuven Leuven Belgium Herbert Irving Comprehensive Center Columbia University Irving Medical Center New York USA Laboratory of Stem Cells and Cancer Université Libre de Bruxelles (ULB) Brussels Belgium Wellcome Trust-MRC Stem Cell Institute University of Cambridge Cambridge UK

Although melanoma is notorious for its high degree of heterogeneity and plasticity1,2,the origin and magnitude of cell-state diversity remains poorly ***,it is unclear whether growth and metastatic dissemination are supported by overlapping or distinct melanoma ***,by combining mouse genetics,single-cell and spatial transcriptomics,lineage tracing and quantitative modelling,we provide evidence of a hierarchical model of tumour growth that mirrors the cellular and molecular logic underlying the cell-fate specification and differentiation of the embryonic neural *** show that tumorigenic competence is associated with a spatially localized perivascular niche,a phenotype acquired through an intercellular communication pathway established by endothelial *** with a model in which only a fraction of cells are fated to fuel growth,temporal single-cell tracing of a population of melanoma cells with a mesenchymal-like state revealed that these cells do not contribute to primary tumour growth but,instead,constitute a pool of metastatic initiating cells that switch cell identity while disseminating to secondary *** data provide a spatially and temporally resolved map of the diversity and trajectories of melanoma cell states and suggest that the ability to support growth and metastasis are limited to distinct pools of *** observation that these phenotypic competencies can be dynamically acquired after exposure to specific niche signals warrant the development of therapeutic strategies that interfere with the cancer cell reprogramming activity of such microenvironmental cues.

关键词： melanoma metastasis organs

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Not at Home on the Range: Peer Production and the Urban/Rural Divide

arXiv

引用

arXiv 2019年

作者： Johnson, Isaac L. Lin, Yilun Jia-Jun Li, Toby Hall, Andrew Halfaker, Aaron Schöning, Johannes Hecht, Brent GroupLens Research Department of Computer Science University of Minnesota Human-Computer Interaction Institute Carnegie Mellon University Wikimedia Foundation Expertise Center for Digital Media Hasselt University - tUL - iMinds

Wikipedia articles about places, OpenStreetMap features, and other forms of peer-produced content have become critical sources of geographic knowledge for humans and intelligent technologies. In this paper, we explore the effectiveness of the peer production model across the rural/urban divide, a divide that has been shown to be an important factor in many online social systems. We find that in both Wikipedia and OpenStreetMap, peer-produced content about rural areas is of systematically lower quality, is less likely to have been produced by contributors who focus on the local area, and is more likely to have been generated by automated software agents (i.e. "bots"). We then codify the systemic challenges inherent to characterizing rural phenomena through peer production and discuss potential solutions. Copyright © 2019, The Authors. All rights reserved.

关键词： Rural areas

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Digital Innovation in Faculty Development: Crafting Academic Portfolios for the Next Era

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Procedia computer science 2024年 246卷 4075-4083页

作者： Hideyuki Kanematsu Akiko Ogawa Takeshi Kogo Risa Kawai Dana M. Barry Nobuyuki Ogawa Shin-nosuke Suzuki Goichi Hagiwara Kayoko Kurita National Institute of Technology (KOSEN) Suzuka College Shiroko-cho Suzuka Mie 510-0294 Dept. Materials & Manufacturing Science Graduate School of Engineering Osaka University 2-1 Yamada-Oka Suita Osaka 565-0871 Japan Faculty of Science Nara Women’s University Uoya Nishimachi Nara 630-8506 Nara Pref. Japan Department of Electrical & Computer Engineering Clarkson University Potsdam/SUNY Canton Canton NY USA National Institute of Technology (KOSEN) Gifu College Kami-makuwa Motosu Gifu 510-0495 Japan National Institute of Technology (KOSEN) 771 Nakakuki Oyama Tochigi 323-0806 Japan Faculty of Human Sciences Kyushu Sangyo University Matsukadai 2-chome Higashi-ku Fukuoka-shi Fukuoka 813-8503 Japan Center for Research and Development in Higher Education the University of Tokyo 7-3-1 Hongo Bunkyo-ku 113-0033m Tokyo Japan

This paper presents one project on integrating digital innovation in faculty development by creating academic portfolios. Academic portfolios document the multifaceted achievements of faculty members and help them in their professional progress and self-evaluation. This initiative adopted a systematic approach following the TU guidelines, incorporating lectures, mentoring, and collaborative sessions, and guiding educators to create portfolios that integrate teaching, research, and service activities. The project’s use of digital tools enabled time efficiency, accessibility, and iterative improvement and improved the transparency and scope of faculty performance. The digital platform also facilitated real-time feedback and integration of the portfolio with a wider digital repository, which aligns with environmentally sustainable practices. Participant feedback highlighted increased motivation and a deeper understanding of the interaction between teaching and research. The project demonstrated that the digital portfolio powerfully aligned teachers’ activities with their professional ethos and promoted continuous development and personal growth goals. This approach suggests the potential for transforming faculty development in the academic community.

关键词： Academic Portfolio faculty development SAP sheet

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A novel fuzzy trust-based secure routing scheme in flying ad hoc networks

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Vehicular Communications 2023年 44卷

作者： Hosseinzadeh, Mehdi Mohammed, Adil Hussein Alenizi, Farhan A. Malik, Mazhar Hussain Yousefpoor, Efat Yousefpoor, Mohammad Sadegh Ahmed, Omed Hassan Rahmani, Amir Masoud Tightiz, Lilia Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Electrical Engineering Department College of Engineering Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia School of Computing and Creative Technologies College of Arts Technology and Environment (CATE) University of the West of England Frenchay Campus Coldharbour Lane Bristol BS16 1QY United Kingdom Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan School of Computing Gachon University 1342 Seongnamdaero Seongnam 13120 South Korea

Today, many studies assess vulnerabilities, threats, and attacks in flying ad hoc networks (FANETs) to provide solutions for countermeasures. Protecting FANETs against attackers and coordinating connections are challenging. The purpose of this study is to increase and maintain communication security. In this paper, a fuzzy trust-based secure routing scheme (FTSR) is presented in FANETs. FTSR utilizes two trust assessment mechanisms, namely local trust and path trust. Local trust strategy is a distributed process for finding reliable neighboring nodes and isolating hostile nodes on the network. In this regard, only reliable nodes are allowed to contribute to the path discovery procedure. This lowers the risk of forming fake paths in FANETs. Path trust strategy is responsible for identifying hostile nodes that are not identified in the local trust process. This strategy shows a general view of the trust status of the desired path. To design this mechanism, the source node runs a fuzzy system to select the safest path between source and the destination. Finally, network simulator 2 (NS2) implements FTSR, and the results such as malicious detection rate, packet delivery ratio, packet loss, accuracy, and delay are obtained from the simulation process. These results indicate that FTSR presents better performance compared to TOPCM, MNRiRIP, and MNDA. However, FTSR takes more time to find paths compared to TOPCM. © 2023 Elsevier Inc.

关键词： Artificial intelligence (AI) Cybersecurity Flying ad hoc networks (FANETs) Fuzzy logic Routing

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Natural Language Processing Markers for Psychosis and Other Psychiatric Disorders: Emerging Themes and Research Agenda From a Cross-Linguistic Workshop

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SCHIZOPHRENIA BULLETIN 2023年第SUPP2期49卷 S86-S92页

作者： Corona Hernandez, Hugo Corcoran, Cheryl Achim, Amelie M. de Boer, Janna N. Boerma, Tessel Brederoo, Sanne G. Cecchi, Guillermo A. Ciampelli, Silvia Elvevag, Brita Fusaroli, Riccardo Giordano, Silvia Hauglid, Mathias van Hessen, Arjan Hinzen, Wolfram Homan, Philipp de Kloet, Sybren F. Koops, Sanne Kuperberg, Gina R. Maheshwari, Kritika Mota, Natalia B. Parola, Alberto Rocca, Roberta Sommer, Iris E. C. Truong, Khiet Voppel, Alban E. van Vugt, Marieke Wijnen, Frank Palaniyappan, Lena Department of Biomedical Sciences of Cells and Systems University Medical Center Groningen University of Groningen Groningen Netherlands Department of Psychiatry Icahn School of Medicine at Mount Sinai NY USA Département de Psychiatrie et Neurosciences VITAM Centre de Recherche en Santé Durable Cervo Brain Research Centre Université Laval Québec Canada Department of Psychiatry University Medical Center Utrecht Utrecht University Utrecht Netherlands Department of Languages Literature and Communication Institute for Language Sciences Utrecht University Utrecht Netherlands University Center of Psychiatry University Medical Center Groningen Groningen Netherlands IBM T. J. Watson Research Center Yorktown Heights NY USA Department of Clinical Medicine University of Tromsø—the Arctic University of Norway Tromsø Norway Department of Linguistics Cognitive Science and Semiotics School of Communication and Culture Aarhus University Aarhus Denmark Department of Culture Interacting Minds Center Cognition and Computation Communication School of Culture and Society Aarhus University Aarhus Denmark Linguistic Data Consortium University of Pennsylvania PA USA Department of Innovative Technologies University of Applied Sciences and Arts of Southern Switzerland Lugano Switzerland Faculty of Law University of Tromsø—the Arctic University of Norway Tromsø Norway Department of Human Media Interaction University of Twente Enschede Netherlands Institució Catalana de Recerca i Estudis Avançats (ICREA) Universitat Pompeu Fabra Barcelona Spain Department of Psychiatry Psychiatric Hospital of the University of Zurich Psychotherapy and Psychosomatics Zurich Switzerland Neurocast BV Amsterdam Netherlands Department of Psychology Tufts University Medford MA USA Department of Psychiatry Harvard Medical School Boston MA USA The Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School Boston MA USA Department of Genetics U

This workshop summary on natural language processing (NLP) markers for psychosis and other psychiatric disorders presents some of the clinical and research issues that NLP markers might address and some of the activities needed to move in that direction. We propose that the optimal development of NLP markers would occur in the context of research efforts to map out the underlying mechanisms of psychosis and other disorders. In this workshop, we identified some of the challenges to be addressed in developing and implementing NLP markers-based Clinical Decision Support Systems (CDSSs) in psychiatric practice, especially with respect to psychosis. Of note, a CDSS is meant to enhance decision-making by clinicians by providing additional relevant information primarily through software (although CDSSs are not without risks). In psychiatry, a field that relies on subjective clinical ratings that condense rich temporal behavioral information, the inclusion of computational quantitative NLP markers can plausibly lead to operationalized decision models in place of idiosyncratic ones, although ethical issues must always be paramount.

关键词： speech technology implementation digital markers psychiatric practice pathophysiology

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Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence

arXiv

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arXiv 2025年

作者： Sun, Yingying Jun, A. Liu, Zhiwei Sun, Rui Qian, Liujia Payne, Samuel H. Bittremieux, Wout Ralser, Markus Li, Chen Chen, Yi Dong, Zhen Perez-Riverol, Yasset Khan, Asif Sander, Chris Aebersold, Ruedi Vizcaíno, Juan Antonio Krieger, Jonathan R. Yao, Jianhua Wen, Han Zhang, Linfeng Zhu, Yunping Xuan, Yue Sun, Benjamin Boyang Qiao, Liang Hermjakob, Henning Tang, Haixu Gao, Huanhuan Deng, Yamin Zhong, Qing Chang, Cheng Bandeira, Nuno Li, Ming Weinan, E. Sun, Siqi Yang, Yuedong Omenn, Gilbert S. Zhang, Yue Xu, Ping Fu, Yan Liu, Xiaowen Overall, Christopher M. Wang, Yu Deutsch, Eric W. Chen, Luonan Cox, Jürgen Demichev, Vadim He, Fuchu Huang, Jiaxing Jin, Huilin Liu, Chao Li, Nan Luan, Zhongzhi Song, Jiangning Yu, Kaicheng Wan, Wanggen Wang, Tai Zhang, Kang Zhang, Le Bell, Peter A. Mann, Matthias Zhang, Bing Guo, Tiannan Affiliated Hangzhou First People’s Hospital State Key Laboratory of Medical Proteomics School of Medicine Westlake University Zhejiang Province Hangzhou China Westlake Center for Intelligent Proteomics Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Province Hangzhou China Biology Department Brigham Young University ProvoUT84602 United States Department of Computer Science University of Antwerp Antwerp2020 Belgium Department of Biochemistry CharitéUniversitätsmedizin Berlin Berlin Germany Biomedicine Discovery Institute Department of Biochemistry and Molecular Biology Monash University MelbourneVICVIC 3800 Australia Wellcome Genome Campus Hinxton CambridgeCB10 1SD United Kingdom Harvard Medical School Ludwig Center at Harvard United States Harvard Medical School Broad Institute Ludwig Center at Harvard Dana-Farber Cancer Institute United States Department of Biology Institute of Molecular Systems Biology ETH Zürich Zürich Switzerland Bruker Ltd. MiltonONL9T 6P4 Canada AI for Life Sciences Lab Tencent Shenzhen518057 China State Key Laboratory of Medical Proteomics AI for Science Institute Beijing100080 China Beijing Institute of Lifeomics Beijing102206 China Thermo Fisher Scientific GmbH Hanna-Kunath Str. 11 Bremen28199 Germany Informatics and Predictive Sciences Research Bristol Myers Squibb United States Department of Chemistry Fudan University Songhu Road 2005 Shanghai200438 China Department of Computer Science Luddy School of Informatics Computing and Engineering Indiana University IN47408 United States ProCan® Children’s Medical Research Institute Faculty of Medicine and Health The University of Sydney WestmeadNSW Australia La Jolla CA United States Central China Institute of Artificial Intelligence University of Waterloo Canada AI for Science Institute Center for Machine Learning Research School of Mathematical Sciences Peking University China Research Institute of Intelligent Complex Systems Fudan U

Artificial intelligence (AI) is transforming scientific research, including proteomics. Advances in mass spectrometry (MS)-based proteomics data quality, diversity, and scale, combined with groundbreaking AI techniques, are unlocking new challenges and opportunities in biological discovery. Here, we highlight key areas where AI is driving innovation, from data analysis to new biological insights. These include developing an AI-friendly ecosystem for proteomics data generation, sharing, and analysis;improving peptide and protein identification and quantification;characterizing protein-protein interactions and protein complexes;advancing spatial and perturbation proteomics;integrating multi-omics data;and ultimately enabling AI-empowered virtual cells. © 2025, CC BY.

关键词： Biotic

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A novel Q-learning-based routing scheme using an intelligent filtering algorithm for flying ad hoc networks (FANETs)

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Journal of King Saud University - computer and Information sciences 2023年第10期35卷

作者： Hosseinzadeh, Mehdi Ali, Saqib Ionescu-Feleaga, Liliana Ionescu, Bogdan-Stefan Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Ahmed, Omed Hassan Rahmani, Amir Masoud Mehmood, Asif Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Accounting and Audit Bucharest University of Economic Studies Bucharest 010374 Romania Department of Management Information System Bucharest University of Economic Studies Bucharest 010374 Romania Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Biomedical Engineering Gachon University Gyeonggi-do Seongnam-si 13120 South Korea

The flying ad hoc network (FANET) is an emerging network focused on unmanned aerial vehicles (UAVs) that has attracted the attention of researchers around the world. Due to the cooperation between UAVs in this network, data transfer between these UAVs is very essential. Routing protocols must determine how to make routing paths for each UAV with others in a wireless ad hoc network to facilitate the data transmission between UAVs. Nowadays, reinforcement learning (RL), especially Q-learning, is an effective response for solving existing challenges in the routing approaches and adding features such as autonomous, self-adaptive, and self-learning to these approaches. In this paper, Q-learning is used to enhance and increase network performance, and a Q-learning-based routing method using an intelligent filtering algorithm called QRF is presented for FANETs. The main innovation in this paper is that QRF manages the size of the state space using the proposed filtering algorithm. This will increase the convergence rate of the Q-learning-based routing algorithm. On the other hand, QRF regulates the learning parameters related to Q-learning so that this scheme is better adapted to the FANET environment. In the last step, the network simulator version 2 (NS2) is employed to execute the simulation process related to QRF. In this process, five evaluation criteria, namely energy consumption, packet delivery rate, overhead, end-to-end delay, and network longevity are evaluated, and the results obtained from QRF are compared with those of QFAN, QTAR, and QGeo. The simulation results in this paper show that QRF makes a balanced energy distribution between UAVs and thus extends the network longevity. Moreover, the intelligent filtering algorithm designed in QRF has reduced delay in the routing process but is associated with communication overhead. © 2023 The Author(s)

关键词： Flying ad hoc networks (FANETs) Q-learning Reinforcement learning (RL) Routing Unmanned aerial vehicles (UAVs)

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Multimodal deep learning framework for image popularity prediction on social media

arXiv

引用

arXiv 2021年

作者： Abousaleh, Fatma S. Cheng, Wen-Huang Yu, Neng-Hao Tsao, Yu Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Electronics Department of Electronics Engineering National Chiao Tung University Hsinchu30010 Taiwan The College of Design Department of Design National Taiwan University of Science and Technology Taipei10607 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan

Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the problem of predicting image popularity on social media. The popularity of an image can be affected by several factors, such as visual content, aesthetic quality, user, post metadata, and time. Thus, considering all these factors is essential for accurately predicting image popularity. In addition, the efficiency of the predictive model also plays a crucial role. In this study, motivated by multimodal learning, which uses information from various modalities, and the current success of convolutional neural networks (CNNs) in various fields, we propose a deep learning model, called visual-social convolutional neural network (VSCNN), which predicts the popularity of a posted image by incorporating various types of visual and social features into a unified network model. VSCNN first learns to extract high-level representations from the input visual and social features by utilizing two individual CNNs. The outputs of these two networks are then fused into a joint network to estimate the popularity score in the output layer. We assess the performance of the proposed method by conducting extensive experiments on a dataset of approximately 432K images posted on Flickr. The simulation results demonstrate that the proposed VSCNN model significantly outperforms state-of-the-art models, with a relative improvement of greater than 2.33%, 7.59%, and 14.16% in terms of Spearman’s Rho, mean absolute error, and mean squared error, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

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Disability in space - What ESA should have aimed for

arXiv

引用

arXiv 2021年

作者： Heinicke, Christiane Kaczmarzyk, Marcin Tannert, Benjamin Wasniowski, Aleksander Perycz, Malgorzata Schöning, Johannes Am Fallturm 2 Bremen28359 Germany Rzeszow University of Technology The Faculty of Civil and Environmental Engineering and Architecture Department of Building Engineering Poznańska Street 2 Rzeszow35-084 Poland Hochschule Bremen - City University of Applied Science Applied Media Informatics Flughafenallee 10 Bremen28199 Germany Space Is More ul. Mikulskiego 17 Wroclaw52-420 Poland Institute of Computer Science Polish Academy of Sciences Department of Artificial Intelligence Lab of Computational Biology Jana Kazimierza 5 st. Warsaw01-248 Poland University of Bremen Human-Computer Interaction Bibliothekstraße 5 Bremen28359 Germany

With announcing their "Parastronaut Feasibility Project", the European Space Agency ESA promises to make every reasonable effort to send astronauts with disability to space. This could spark hope in the 15% of all people who live with some form of disability. However, the fine-print of the announcement sets overly tight boundaries to "acceptable" disabilities, allowing only malformations that are expected to have a positive impact on the parastronaut's performance in space. By doing so, ESA is following decade-old traditions in space flight, with some inclusion for the sake of inclusion and public opinion. Instead of accommodating people with disabilities, ESA should send a strong signal for inclusion and truly challenge people with disabilities so they can and will tease out the best of their qualities. © 2021, CC BY.

关键词： Manned space flight

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Longitudinal Complex Dynamics of Labour Markets Reveal Increasing Polarisation

arXiv

引用

arXiv 2022年

作者： Althobaiti, Shahad Alabdulkareem, Ahmad Shen, Judy Hanwen Rahwan, Iyad Frank, Morgan Moro, Esteban Rutherford, Alex Riyadh Saudi Arabia Intelmatix Intelligent Informatics Technologies CambridgeMA United States Computer Science Department Stanford University CA United States Center for Humans and Machines Max Planck Institute for Human Development Berlin Germany Department of Informatics and Networked Systems University of Pittsburgh PittsburghPA United States Digital Economy Lab Institute for Human-Centered Artificial Intelligence Stanford University StanfordCA United States Media Laboratory Massachusetts Institute of Technology CambridgeMA United States Department of Mathematics & GISC Universidad Carlos III de Madrid Leganes Spain Institute for Data Systems and Society Massachusetts Institute of Technology CambridgeMA United States

In this paper we conduct a longitudinal analysis of the structure of labour markets in the US over 7 decades of technological, economic and policy change. We make use of network science, natural language processing and machine learning to uncover structural changes in the labour market over time. We find a steady rate of both disappearance of jobs and a shift in the required work tasks, despite much technological and economic change over this time period. Machine learning is used to classify jobs as being predominantly cognitive or physical based on the textual description of the workplace tasks. We also measure increasing polarisation between these two classes of jobs, linked by the similarity of tasks, over time that could constrain workers wishing to move to different jobs. © 2022, CC BY.

关键词： Employment

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