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Warburg Effects in Cancer and Normal Proliferating Cells:Two Tales of the Same Name

Genomics, Proteomics & Bioinformatics 2019年第3期17卷 273-286页

作者： Huiyan Sun Liang Chen Sha Cao Yanchun Liang Ying Xu The China-Japan Union Hospital Jilin UniversityChangchun 130033China MOE Key Laboratory of Symbolic Computation and Knowledge Engineering College of Computer Science and TechnologyJilin UniversityChangchun 130012China Computational Systems Biology Lab Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of GeorgiaAthensGA 30602USA Faculty of Health Sciences University of MacaoTaipaMacao SAR 999078China Department of Biostatistics School of MedicineIndiana UniversityIndianapolisIN 46202USA Zhuhai Laboratory of MOE Key Laboratory of Symbolic Computation and Knowledge Engineering Zhuhai College of Jilin UniversityZhuhai 519041China

It has been observed that both cancer tissue cells and normal proliferating cells(NPCs)have the Warburg *** goal here is to demonstrate that they do this for different *** accomplish this,we have analyzed the transcriptomic data of over 7000 cancer and control tissues of 14 cancer types in TCGA and data of five NPC types in *** analyses reveal that NPCs accumulate large quantities of ATPs produced by the respiration process before starting the Warburg effect,to raise the intracellular pH from 6.8 to 7.2 and to prepare for cell division *** cell cycle starts,the cells start to rely on glycolysis for ATP generation followed by ATP hydrolysis and lactic acid release,to maintain the elevated intracellular pH as needed by cell division since together the three processes are pH *** cells go back to the normal respirationbased ATP production once the cell division phase *** comparison,cancer cells have reached their intracellular pH at 7.4 from top down as multiple acid-loading transporters are up-regulated and most acid-extruding ones except for lactic acid exporters are *** cells use continuous glycolysis for ATP production as way to acidify the intracellular space since the lactic acid secretion is decoupled from glycolysis-based ATP generation and is pH balanced by increased expressions of acid-loading ***-expression analyses suggest that lactic acid secretion is regulated by external,non-pH related ***,our data strongly suggest that the two cell types have the Warburg effect for very different reasons.

关键词： Cancer Warburg effect Fenton reaction Cell proliferation pH homeostasis

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A framework of biomarkers for skeletal aging: a consensus statement by the Aging Biomarker Consortium

Life Medicine

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Life Medicine 2023年第6期2卷 1页

作者： Aging Biomarker Consortium,Jinlong Suo Yibo Gan Yangli Xie Shuqin Xu Jianfang Wang Di Chen Lin Chen Lianfu Deng Shiqing Feng Jingdong Jackie Han Qing Jiang Guanghua Lei Peng Liu Xianghang Luo Xin Ma Jing Qu Chunli Song Peifu Tang Tingting Tang Sijia Wang Xiaochun Wei Chengtie Wu Guozhi Xiao Liu Yang Licheng Zhang Weiqi Zhang Zhenlin Zhang Guang-Hui Liu Changqing Zhang Gang Pei Jian Luo Rui Yue Weiguo Zou Department of Orthopedic Surgery Institute of Microsurgery on Extremities Shanghai Sixth People?s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China State Key Laboratory of Trauma and Chemical Poisoning Department of Spine Surgery Center of Orthopedics Daping Hospital Army Medical University (Third Military Medical University) Chongqing China State Key Laboratory of Trauma and Chemical Poisoning Department of Wound Repair and Rehabilitation Medicine Center of Bone Metabolism and Repair (CBMR) Daping Hospital Army Medical University (Third Military Medical University) Chongqing China Department of Osteoporosis and Bone Diseases Shanghai Clinical Research Center of Bone Disease Shanghai Sixth People?s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Shanghai Key Laboratory of Signaling and Disease Research Frontier Science Center for Stem Cell Research School of Life Sciences and Technology Institute for Regenerative Medicine Shanghai East Hospital Tongji University Shanghai China Research Center for Computer-Aided Drug Discovery Faculty of Pharmaceutical Sciences Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Shanghai Key Laboratory for Prevention and Treatment of Bone and Joint Diseases Department of Orthopaedics Shanghai Institute of Traumatology and Orthopaedics Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Department of Orthopaedics Qilu Hospital of Shandong University Shandong University Centre for Orthopaedics Advanced Medical Research Institute Cheeloo College of Medicine Shandong University Jinan China Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Center for Quantitative Biology (CQB) Peking University Beijing China State Key Laboratory of Pharmaceutical Biotechnology Division of Sports Medicine and Adult Reconstructive Surgery Department of Orthopedic Surgery Drum Towe

The skeleton is an important structural and metabolic organ in human body, while aging is the physiological basis for degenerative skeletal diseases. China has the largest aging population in the world and faces great challenges in preventing and managing diseases related to skeletal aging. To address these challenges, the Aging China Biomarkers Consortium (ABC) has reached an expert consensus on biomarkers of skeletal aging by synthesizing the literature and insights from scientists and clinicians. The consensus provides a comprehensive assessment of biomarkers associated with skeletal aging and proposes a systematic framework that categorizes biomarkers into three dimensions, namely, functional, structural, and humoral dimensions. Within each dimension, the ABC recommended clinical and evidential research-based biomarkers for physiological aging and degenerative pathologies of the skeleton. This expert consensus aims to lay the foundation for future studies to assess the prediction, diagnosis, early warning, and treatment of diseases associated with skeletal aging, with the ultimate goal of improving the skeletal health of elderly populations in China and around the world.

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Recovering the star formation histories of recently-quenched galaxies: the impact of model and prior choices

arXiv

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arXiv 2022年

作者： Suess, Katherine A. Leja, Joel Johnson, Benjamin D. Bezanson, Rachel Greene, Jenny E. Kriek, Mariska Lower, Sidney Narayanan, Desika Setton, David J. Spilker, Justin S. Department of Astronomy and Astrophysics University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States Department of Astronomy & Astrophysics The Pennsylvania State University University ParkPA16802 United States Institute for Computational & Data Sciences The Pennsylvania State University University ParkPA United States Institute for Gravitation and the Cosmos The Pennsylvania State University University ParkPA16802 United States Center for Astrophysics Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Department of Physics and Astronomy PITT PACC University of Pittsburgh PittsburghPA15260 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States Leiden Observatory Leiden University P.O.Box 9513 LeidenNL-2300 AA Netherlands Astronomy Department University of California BerkeleyCA94720 United States Department of Astronomy University of Florida 211 Bryant Space Science Center GainesvilleFL32611 United States University of Florida Informatics Institute 432 Newell Drive CISE Bldg E251 GainesvilleFL32611 United States Cosmic Dawn Centre The Niels Bohr Institue University of Copenhagen and DTU-Space Technical University of Denmark Denmark Department of Physics and Astronomy George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy Texas A&M University 4242 TAMU College StationTX77843-4242 United States

Accurate models of the star formation histories (SFHs) of recently-quenched galaxies can provide constraints on when and how galaxies shut down their star formation. The recent development of "nonparametric" SFH models promises the flexibility required to make these measurements. However, model and prior choices significantly affect derived SFHs, particularly for post-starburst galaxies (PSBs) which have sharp changes in their recent SFH. In this paper, we create mock PSBs, then use the Prospector SED fitting software to test how well four different SFH models recover key properties. We find that a two-component parametric model performs well for our simple mock galaxies, but is sensitive to model mismatches. The fixed- and flexible-bin non-parametric models included in Prospector are able to rapidly quench a major burst of star formation, but systematically underestimate the post-burst age by up to 200 Myr. We develop a custom SFH model that allows for additional flexibility in the recent SFH. Our flexible non-parametric model is able to constrain post-burst ages with no significant offset and just ∼ 90 Myr of scatter. Our results suggest that while standard non-parametric models are able to recover first-order quantities of the SFH (mass, SFR, average age), accurately recovering higher-order quantities (burst fraction, quenching time) requires careful consideration of model flexibility. These mock recovery tests are a critical part of future SFH studies. Finally, we show that our new, public SFH model is able to accurately recover the properties of mock star-forming and quiescent galaxies and is suitable for broader use in the SED fitting community. § Copyright © 2022, The Authors. All rights reserved.

关键词： Quenching

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Learning physically consistent mathematical models from data using group sparsity

arXiv

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arXiv 2020年

作者： Maddu, Suryanarayana Cheeseman, Bevan L. Müller, Christian L. Sbalzarini, Ivo F. Technische Universität Dresden Faculty of Computer Science Dresden01069 Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden01307 Germany Center for Systems Biology Dresden Dresden01307 Germany Center for Computational Mathematics Flatiron Institute New YorkNY United States Department of Statistics LMU München Munich Germany Institute of Computational Biology Helmholtz Zentrum München Germany Center for Scalable Data Analytics and Artificial Intelligence ScaDS.AI Dresden/Leipzig Germany Cluster of Excellence Physics of Life TU Dresden Germany

We propose a statistical learning framework based on group-sparse regression that can be used to 1) enforce conservation laws, 2) ensure model equivalence, and 3) guarantee symmetries when learning or inferring differential-equation models from measurement data. Directly learning interpretable mathematical models from data has emerged as a valuable modeling approach. However, in areas like biology, high noise levels, sensor-induced correlations, and strong inter-system variability can render data-driven models nonsensical or physically inconsistent without additional constraints on the model structure. Hence, it is important to leverage prior knowledge from physical principles to learn "biologically plausible and physically consistent" models rather than models that simply fit the data best. We present a novel group Iterative Hard Thresholding (gIHT) algorithm and use stability selection to infer physically consistent models with minimal parameter tuning. We show several applications from systems biology that demonstrate the benefits of enforcing priors in data-driven modeling. © 2020, CC BY.

关键词： Iterative methods

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SI-spreading-based network embedding in static and temporal networks

arXiv

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arXiv 2020年

作者： Zhan, Xiu-Xiu Li, Ziyu Masuda, Naoki Holme, Petter Wang, Huijuan Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands Department of Mathematics University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8503 Japan

Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a similarity comparison task. Nodes with similar embedding vectors are more likely to be connected. Classic network embedding algorithms are random-walk-based. They sample trajectory paths via random walks and generate node pairs from the trajectory paths. The node pair set is further used as the input for a Skip-Gram model, a representative language model that embeds nodes (which are regarded as words) into vectors. In the present study, we propose to replace random walk processes by a spreading process, namely the susceptible-infected (SI) model, to sample paths. Specifically, we propose two SI-spreading-based algorithms, SINE and TSINE, to embed static and temporal networks, respectively. The performance of our algorithms is evaluated by the missing link prediction task in comparison with state-of-the-art static and temporal network embedding algorithms. Results show that SINE and TSINE outperform the baselines across all six empirical datasets. We further find that the performance of SINE is mostly better than TSINE, suggesting that temporal information does not necessarily improve the embedding for missing link prediction. Moreover, we study the effect of the sampling size, quantified as the total length of the trajectory paths, on the performance of the embedding algorithms. The better performance of SINE and TSINE requires a smaller sampling size in comparison with the baseline algorithms. Hence, SI-spreading-based embedding tends to be more applicable to large-scale networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Network embeddings

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A Survey on Edge Detection based recent Marine Horizon Line Detection Methods and their Applications

A Survey on Edge Detection based recent Marine Horizon Line ...

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International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)

作者： Manzoor Ahmed Hashmani Muhammad Umair Syed Sajjad Hussain Rizvi Abdul Rehman Gilal High-Performance Cloud Computing Center (HPC3) Center for Research in Data Science (CERDAS) Universiti Teknologi PETRONAS Seri Iskandar Malaysia High-Performance Cloud Computing Center (HPC3) Universiti Teknologi PETRONAS Seri Iskandar Malaysia Faculty of Engineering Sciences and Technology Hamdard University Karachi Pakistan Department of Computer Science Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9781728149707

ISBN: (纸本)9781728149714

Sea and sky boundary identification (i.e. marine horizon line detection) from a marine image is a problem of great interest for reasons such as, unmanned surface or aerial vehicle navigation, surveillance by object detection and tracking, and determining the spatial orientation of the ship. Due to the complexity of the marine environment, the problem poses its own unique challenges. In recent years, different methods have been proposed by the researchers to solve the problem. Those methods can be grouped into two categories; (i) edge detection based horizon detection, and (ii) machine learning-based horizon detection. In this paper, we present a survey on edge detection based recent marine horizon line detection methods and their applications. We have selected studies from the previous three years and discussed each study's approach to marine horizon line detection issue, the datasets used for testing purposes and its results. The authors' observations for each study are presented with a recommendation for their suitability for a specific application in the marine environment. Findings of the survey and future research directions for the researchers are also identified and presented. We hope that this survey paper provides a comprehensive overview of edge detection based recent marine horizon line detection methods and help the researchers in exploring new solutions to this challenging problem.

关键词： Image edge detection Transforms Gray-scale Feature extraction Real-time systems computational efficiency Image color analysis

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The COSMOS-Web Lens Survey (COWLS) III: forecasts versus data

arXiv

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arXiv 2025年

作者： Hogg, Natalie B. Nightingale, James W. He, Quihan McCleary, Jacqueline Mahler, Guillaume Amvrosiadis, Aristeidis Gozaliasl, Ghassem Berman, Edward Massey, Richard J. Scognamiglio, Diana Franco, Maximilien Liu, Daizhong Shuntov, Marko Paquereau, Louise Ilbert, Olivier Allen, Natalie Toft, Sune Akins, Hollis B. Casey, Caitlin M. Kartaltepe, Jeyhan S. Koekemoer, Anton M. McCracken, Henry Joy Rhodes, Jason D. Robertson, Brant E. Drakos, Nicole E. Faisst, Andreas L. Hatamnia, Hossein Newman, Sophie L. Laboratoire Univers et Particules de Montpellier CNRS Université de Montpellier Parvis Alexander Grothendieck Montpellier34090 France School of Mathematics Statistics and Physics Newcastle University Herschel Building Newcastle-upon-TyneNE1 7RU United Kingdom Department of Physics Institute for Computational Cosmology Durham University South Road DurhamDH1 3LE United Kingdom Department of Physics Northeastern University 360 Huntington Ave BostonMA United States STAR Institute Quartier Agora - Allée du six Août Liège19c B-4000 Belgium Department of Physics Centre for Extragalactic Astronomy Durham University South Road DurhamDH1 3LE United Kingdom Department of Computer Science Aalto University PO Box 15400 EspooFI-00 076 Finland Department of Physics Faculty of Science University of Helsinki Helsinki00014 Finland Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA United States Department of Astronomy The University of Texas at Austin AustinTX United States Purple Mountain Observatory Chinese Academy of Sciences 10 Yuanhua Road Nanjing210023 China Denmark Niels Bohr Institute University of Copenhagen Jagtvej 128 Copenhagen2200 Denmark Institut d’Astrophysique de Paris UMR 7095 CNRS Sorbonne Université 98 bis boulevard Arago ParisF-75014 France Laboratoire d’astrophysique de Marseille Aix Marseille University CNRS CNES Marseille France Department of Phyiscs University of California CA Santa BarbaraCA93106 United States Laboratory for Multiwavelength Astrophysics School of Physics and Astronomy Rochester Institute of Technology 84 Lomb Memorial Drive RochesterNY14623 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Department of Astronomy and Astrophysics University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States Department of Physics and Astronomy University of Hawaii Hilo 200 W Kawili St Hilo

We compare forecasts for the abundance and properties of strong gravitational lenses in the COSMOS-Web survey, a 0.54 deg2 survey of the COSMOS field using the NIRCam and MIRI instruments aboard JWST, with the first catalogue of strong lens candidates identified in the observed NIRCam data, COWLS. We modify the lenspop package to produce a forecast for strong lensing in COSMOS-Web. We add a new mock galaxy catalogue to use as the source population, as well as the COSMOS-Web survey specifications, including the transmission data for the four NIRCam filters used. We forecast 107 strong lenses can be detected in COSMOS-Web across all bands, assuming complete subtraction of the lens galaxy light. The majority of the lenses are forecast to have small Einstein radii (θE © 2025, CC BY.

关键词： Statistical mechanics

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Optimal L p -approximation of convex sets by convex subsets

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Nonlinear Analysis 2025年 261卷

作者： Zakaria Fattah Ilias Ftouhi Enrique Zuazua SMARTiLab Laboratory Moroccan School of Engineering Sciences (EMSI) Rabat Morocco Mathematics and Computer Science Department ENSAM of Meknes University of Moulay Ismail Marjane II AL Mansour B.P. 15290 50050 Meknes Morocco Chair for Dynamics Control Machine Learning and Numerics Alexander von Humboldt-Professorship Department of Mathematics Friedrich-Alexander-Universität Erlangen-Nürnberg 91058 Erlangen Germany King Fahd University of Petroleum and Minerals Department of Mathematics 31261 Dhahran Saudi Arabia Chair of Computational Mathematics Fundación Deusto Av. de las Universidades 24 48007 Bilbao Basque Country Spain Departamento de Matemáticas Universidad Autónoma de Madrid 28049 Madrid Spain

Given a convex set Ω of R n , we consider the shape optimization problem of finding a convex subset ω ⊂ Ω , of a given measure, minimizing the p -distance functional J p ( ω ) ≔ ∫ S n − 1 | h Ω − h ω | p d H n − 1 1 p , where 1 ≤ p < ∞ and h ω and h Ω are the support functions of ω and the fixed container Ω , respectively. We prove the existence of solutions and show that this minimization problem Γ -converges, when p tends to + ∞ , towards the problem of finding a convex subset ω ⊂ Ω , of a given measure, minimizing the Hausdorff distance to the convex Ω . In the planar case, we show that the free parts of the boundary of the optimal shapes, i.e., those that are in the interior of Ω , are given by polygonal lines. Still in the 2D setting, from a computational perspective, the classical method based on optimizing Fourier coefficients of support functions is not efficient, as it is unable to efficiently capture the presence of segments on the boundary of optimal shapes. We subsequently propose a method combining Fourier analysis and a numerical scheme recently introduced in Bogosel (2023), allowing to obtain accurate results, as demonstrated through numerical experiments.

关键词： Convex geometry-shape optimization

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Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing

arXiv

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arXiv 2019年

作者： Chen, Jianguo Li, Kenli Deng, Qingying Li, Keqin Yu, Philip S. College of Computer Science and Electronic Engineering Hunan University National Supercomputing Center in Changsha Hunan Changsha410082 China School of Mathematics and Computational Science Xiangtan University Xiangtan411105 China Department of Computer Science State University of New York New PaltzNY12561 United States Department of Computer Science University of Illinois at Chicago ChicagoIL60607 United States Institute for Data Science Tsinghua University Beijing100084 China

In this paper, we propose a Distributed Intelligent Video Surveillance (DIVS) system using Deep Learning (DL) algorithms and deploy it in an edge computing environment. We establish a multi-layer edge computing architecture and a distributed DL training model for the DIVS system. The DIVS system can migrate computing workloads from the network center to network edges to reduce huge network communication overhead and provide low-latency and accurate video analysis solutions. We implement the proposed DIVS system and address the problems of parallel training, model synchronization, and workload balancing. Task-level parallel and model-level parallel training methods are proposed to further accelerate the video analysis process. In addition, we propose a model parameter updating method to achieve model synchronization of the global DL model in a distributed EC environment. Moreover, a dynamic data migration approach is proposed to address the imbalance of workload and computational power of edge nodes. Experimental results showed that the EC architecture can provide elastic and scalable computing power, and the proposed DIVS system can efficiently handle video surveillance and analysis tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Edge computing

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The bulk van der Waals layered magnet CrSBr is a quasi-1D material

arXiv

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arXiv 2022年

作者： Klein, Julian Pingault, Benjamin Florian, Matthias Heißenbüttel, Marie-Christin Steinhoff, Alexander Song, Zhigang Torres, Kierstin Dirnberger, Florian Curtis, Jonathan B. Weile, Mads Penn, Aubrey Deilmann, Thorsten Dana, Rami Bushati, Rezlind Quan, Jiamin Luxa, Jan Sofer, Zdenek Alù, Andrea Menon, Vinod M. Wurstbauer, Ursula Rohlfing, Michael Narang, Prineha Lončar, Marko Ross, Frances M. Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States QuTech Delft University of Technology Delft2600 GA Netherlands Department of Electrical and Computer Engineering Department of Physics University of Michigan Ann ArborMI48109 United States Institut für Festkörpertheorie Westfälische Wilhelms-Universität Münster Münster48149 Germany Institut für Theoretische Physik Universität Bremen P.O. Box 330 440 Bremen28334 Germany Bremen Center for Computational Materials Science University of Bremen Bremen28359 Germany Department of Physics City College of New York New YorkNY10031 United States College of Letters and Science UCLA Los AngelesCA90095 United States Department of Physics Technical University of Denmark Kgs. LyngbyDK-2800 Denmark MIT.nano Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics The Graduate Center City University of New York New YorkNY10016 United States Photonics Initiative CUNY Advanced Science Research Center New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10026 United States Department of Inorganic Chemistry University of Chemistry and Technology Prague Technická 5 Prague 6166 28 Czech Republic Institute of Physics Center for Nanotechnology University of Münster Münster48149 Germany

Correlated quantum phenomena in one-dimensional (1D) systems that exhibit competing electronic and magnetic order are of strong interest for studying fundamental interactions and excitations, such as Tomonaga-Luttinger liquids and topological orders and defects with properties completely different from the quasiparticles expected in their higher-dimensional counterparts. However, clean 1D electronic systems are difficult to realize experimentally, particularly magnetically ordered systems. Here, we show that the van der Waals layered magnetic semiconductor CrSBr behaves like a quasi-1D material embedded in a magnetically ordered environment. The strong 1D electronic character originates from the Cr-S chains and the combination of weak interlayer hybridization and anisotropy in effective mass and dielectric screening with an effective electron mass ratio of meX/meY ∼ 50. This extreme anisotropy experimentally manifests in strong electron-phonon and exciton-phonon interactions, a Peierls-like structural instability and a Fano resonance from a van Hove singularity of similar strength of metallic carbon nanotubes. Moreover, due to the reduced dimensionality and interlayer coupling, CrSBr hosts spectrally narrow (1 meV) excitons of high binding energy and oscillator strength that inherit the 1D character. Overall, CrSBr is best understood as a stack of weakly hybridized monolayers and appears to be an experimentally attractive candidate for the study of exotic exciton and 1D correlated many-body physics in the presence of magnetic order. Copyright © 2022, The Authors. All rights reserved.

关键词： Excitons

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