arXiv - QuanBio - Cell Behavior最新文献_第4页

Gradient sensing limit of a cell when controlling the elongating direction 控制拉伸方向时电池的梯度感应极限

arXiv - QuanBio - Cell Behavior Pub Date : 2024-05-08 DOI: arxiv-2405.04810

Kento Nakamura, Tetsuya J. Kobayashi

{"title":"Gradient sensing limit of a cell when controlling the elongating direction","authors":"Kento Nakamura, Tetsuya J. Kobayashi","doi":"arxiv-2405.04810","DOIUrl":"https://doi.org/arxiv-2405.04810","url":null,"abstract":"Eukaryotic cells perform chemotaxis by determining the direction of chemical\u0000gradients based on stochastic sensing of concentrations at the cell surface. To\u0000examine the efficiency of this process, previous studies have investigated the\u0000limit of estimation accuracy for gradients. However, these studies assume that\u0000the cell shape and gradient are constant, and do not consider how adaptive\u0000regulation of cell shape affects the estimation limit. Dynamics of cell shape\u0000during gradient sensing is biologically ubiquitous and can influence the\u0000estimation by altering the way the concentration is measured, and cells may\u0000strategically regulate their shape to improve estimation accuracy. To address\u0000this gap, we investigate the estimation limits in dynamic situations where\u0000cells change shape adaptively depending on the sensed signal. We approach this\u0000problem by analyzing the stationary solution of the Bayesian nonlinear\u0000filtering equation. By applying diffusion approximation to the ligand-receptor\u0000binding process and the Laplace method for the posterior expectation under a\u0000high signal-to-noise ratio regime, we obtain an analytical expression for the\u0000estimation limit. This expression indicates that estimation accuracy can be\u0000improved by elongating perpendicular to the estimated direction, which is also\u0000confirmed by numerical simulations. Our analysis provides a basis for\u0000clarifying the interplay between estimation and control in gradient sensing and\u0000sheds light on how cells optimize their shape to enhance chemotactic\u0000efficiency.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140928972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Clustering and spatial distribution of mitochondria in dendritic trees 树突树中线粒体的聚类和空间分布

arXiv - QuanBio - Cell Behavior Pub Date : 2024-05-07 DOI: arxiv-2405.04684

Mario Hidalgo-Soria, Elena F. Koslover

引用次数: 0

Proliferation-driven mechanical feedback regulates cell dynamics in growing tissues 增殖驱动的机械反馈调节生长组织中的细胞动力学

arXiv - QuanBio - Cell Behavior Pub Date : 2024-05-03 DOI: arxiv-2405.01960

Sumit Sinha, Xin Li, Abdul N Malmi-Kakkada, D. Thirumalai

{"title":"Proliferation-driven mechanical feedback regulates cell dynamics in growing tissues","authors":"Sumit Sinha, Xin Li, Abdul N Malmi-Kakkada, D. Thirumalai","doi":"arxiv-2405.01960","DOIUrl":"https://doi.org/arxiv-2405.01960","url":null,"abstract":"Local stresses in a tissue, a collective property, regulate cell division and\u0000apoptosis. In turn, cell growth and division induce active stresses in the\u0000tissue. As a consequence, there is a feedback between cell growth and local\u0000stresses. However, how the cell dynamics depend on local stress-dependent cell\u0000division and the feedback strength is not fully understood. Here, we probe the\u0000consequences of stress-mediated growth and cell division on cell dynamics using\u0000agent-based simulations of a two-dimensional growing tissue. We discover a rich\u0000dynamical behavior of individual cells, ranging from jamming (mean square\u0000displacement, $Delta (t) sim t^{alpha}$ with $alpha$ less than unity), to\u0000hyperdiffusion ($alpha > 2$) depending on cell division rate and the strength\u0000of the mechanical feedback. Strikingly, $Delta (t)$ is determined by the\u0000tissue growth law, which quantifies cell proliferation (number of cells $N(t)$\u0000as a function of time). The growth law ($N(t) sim t^{lambda}$ at long times)\u0000is regulated by the critical pressure that controls the strength of the\u0000mechanical feedback and the ratio between cell division-apoptosis rates. We\u0000show that $lambda sim alpha$, which implies that higher growth rate leads to\u0000a greater degree of cell migration. The variations in cell motility are linked\u0000to the emergence of highly persistent forces extending over several cell cycle\u0000times. Our predictions are testable using cell-tracking imaging techniques.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140881734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing Biomedical Applications: Antioxidant and Biocompatible Cerium Oxide Nanoparticle-Integrated Poly-ε- caprolactone Fibers 推进生物医学应用：抗氧化和生物相容性氧化铈纳米粒子集成聚-ε-己内酯纤维

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-26 DOI: arxiv-2404.17091

Ummay Mowshome Jahan, Brianna Blevins, Sergiy Minko, Vladimir Reukov

{"title":"Advancing Biomedical Applications: Antioxidant and Biocompatible Cerium Oxide Nanoparticle-Integrated Poly-ε- caprolactone Fibers","authors":"Ummay Mowshome Jahan, Brianna Blevins, Sergiy Minko, Vladimir Reukov","doi":"arxiv-2404.17091","DOIUrl":"https://doi.org/arxiv-2404.17091","url":null,"abstract":"Reactive oxygen species (ROS), which are expressed at high levels in many\u0000diseases, can be scavenged by cerium oxide nanoparticles (CeO2NPs). CeO2NPs can\u0000cause significant cytotoxicity when administered directly to cells, but this\u0000cytotoxicity can be reduced if CeO2NPs can be encapsulated in biocompatible\u0000polymers. In this study, CeO2NPs were synthesized using a one-stage process,\u0000then purified, characterized, and then encapsulated into an electrospun\u0000poly-{epsilon}-caprolactone (PCL) scaffold. The direct administration of\u0000CeO2NPs to RAW 264.7 Macrophages resulted in reduced ROS levels but lower cell\u0000viability. Conversely, the encapsulation of nanoceria in a PCL scaffold was\u0000shown to lower ROS levels and improve cell survival. The study demonstrated an\u0000effective technique for encapsulating nanoceria in PCL fiber and confirmed its\u0000biocompatibility and efficacy. This system has the potential to be utilized for\u0000developing tissue engineering scaffolds, targeted delivery of therapeutic\u0000CeO2NPs, wound healing, and other biomedical applications.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140808830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unraveling cell-cell communication with NicheNet by inferring active ligands from transcriptomics data 通过转录组学数据推断活性配体，利用 NicheNet 揭开细胞间通讯的神秘面纱

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-25 DOI: arxiv-2404.16358

Chananchida Sang-aram, Robin Browaeys, Ruth Seurinck, Yvan Saeys

{"title":"Unraveling cell-cell communication with NicheNet by inferring active ligands from transcriptomics data","authors":"Chananchida Sang-aram, Robin Browaeys, Ruth Seurinck, Yvan Saeys","doi":"arxiv-2404.16358","DOIUrl":"https://doi.org/arxiv-2404.16358","url":null,"abstract":"Ligand-receptor interactions constitute a fundamental mechanism of cell-cell\u0000communication and signaling. NicheNet is a well-established computational tool\u0000that infers ligand-receptor interactions that potentially regulate gene\u0000expression changes in receiver cell populations. Whereas the original\u0000publication delves into the algorithm and validation, this paper describes a\u0000best practices workflow cultivated over four years of experience and user\u0000feedback. Starting from the input single-cell expression matrix, we describe a\u0000\"sender-agnostic\" approach which considers ligands from the entire\u0000microenvironment, and a \"sender-focused\" approach which only considers ligands\u0000from cell populations of interest. As output, users will obtain a list of\u0000prioritized ligands and their potential target genes, along with multiple\u0000visualizations. In NicheNet v2, we have updated the data sources and\u0000implemented a downstream procedure for prioritizing cell-type-specific\u0000ligand-receptor pairs. Although a standard NicheNet analysis takes less than 10\u0000minutes to run, users often invest additional time in making decisions about\u0000the approach and parameters that best suit their biological question. This\u0000paper serves to aid in this decision-making process by describing the most\u0000appropriate workflow for common experimental designs like case-control and cell\u0000differentiation studies. Finally, in addition to the step-by-step description\u0000of the code, we also provide wrapper functions that enable the analysis to be\u0000run in one line of code, thus tailoring the workflow to users at all levels of\u0000computational proficiency.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-scale modeling of Snail-mediated response to hypoxia in tumor progression 肿瘤进展过程中蜗牛介导的缺氧反应的多尺度建模

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-25 DOI: arxiv-2404.16769

Giulia Chiari, Martina Conte, Marcello Delitala

{"title":"Multi-scale modeling of Snail-mediated response to hypoxia in tumor progression","authors":"Giulia Chiari, Martina Conte, Marcello Delitala","doi":"arxiv-2404.16769","DOIUrl":"https://doi.org/arxiv-2404.16769","url":null,"abstract":"Tumor cell migration within the microenvironment is a crucial aspect for\u0000cancer progression and, in this context, hypoxia has a significant role. An\u0000inadequate oxygen supply acts as an environmental stressor inducing migratory\u0000bias and phenotypic changes. In this paper, we propose a novel multi-scale\u0000mathematical model to analyze the pivotal role of Snail protein expression in\u0000the cellular responses to hypoxia. Starting from the description of single-cell\u0000dynamics driven by the Snail protein, we construct the corresponding kinetic\u0000transport equation that describes the evolution of the cell distribution.\u0000Subsequently, we employ proper scaling arguments to formally derive the\u0000equations for the statistical moments of the cell distribution, which govern\u0000the macroscopic tumor dynamics. Numerical simulations of the model are\u0000performed in various scenarios with biological relevance to provide insights\u0000into the role of the multiple tactic terms, the impact of Snail expression on\u0000cell proliferation, and the emergence of hypoxia-induced migration patterns.\u0000Moreover, quantitative comparison with experimental data shows the model's\u0000reliability in measuring the impact of Snail transcription on cell migratory\u0000potential. Through our findings, we shed light on the potential of our\u0000mathematical framework in advancing the understanding of the biological\u0000mechanisms driving tumor progression.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electroporation-mediated Metformin for effective anticancer treatment of triple-negative breast cancer cells 电穿孔介导二甲双胍对三阴性乳腺癌细胞的有效抗癌治疗

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-22 DOI: arxiv-2404.14353

Praveen Sahu, Ignacio G. Camarillo, Pragatheiswar Giri, Raji Sundararajan

引用次数: 0

Wave-driven phase wave patterns in a ring of FitzHugh-Nagumo oscillators 菲茨休-纳古莫振荡器环中的波驱动相位波模式

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-20 DOI: arxiv-2404.13363

Daniel Cebrián-Lacasa, Marcin Leda, Andrew B. Goryachev, Lendert Gelens

引用次数: 0

Travelling waves in a minimal go-or-grow model of cell invasion 细胞入侵最小化或增长模型中的游动波

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-17 DOI: arxiv-2404.11251

Carles Falcó, Rebecca M. Crossley, Ruth E. Baker

引用次数: 0

Modelling adhesion in stochastic and mean-field models of cell migration 细胞迁移随机模型和平均场模型中的粘附建模

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-15 DOI: arxiv-2404.10120

Shahzeb Raja Noureen, Richard L. Mort, Christian A. Yates

{"title":"Modelling adhesion in stochastic and mean-field models of cell migration","authors":"Shahzeb Raja Noureen, Richard L. Mort, Christian A. Yates","doi":"arxiv-2404.10120","DOIUrl":"https://doi.org/arxiv-2404.10120","url":null,"abstract":"Adhesion between cells plays an important role in many biological processes\u0000such as tissue morphogenesis and homeostasis, wound healing and cancer cell\u0000metastasis. From a mathematical perspective, adhesion between multiple cell\u0000types has been previously analysed using discrete and continuum models\u0000including the Cellular Potts models and partial differential equations (PDEs).\u0000While these models can represent certain biological situations well, Cellular\u0000Potts models can be computationally expensive and continuum models only capture\u0000the macroscopic behaviour of a population of cells, ignoring stochasticity and\u0000the discrete nature of cell dynamics. Cellular automaton models allow us to\u0000address these problems and can be used for a wide variety of biological\u0000systems. In this paper, we consider a cellular automaton approach and develop\u0000an on-lattice agent-based model (ABM) for cell migration and adhesion in a\u0000population composed of two cell types. By deriving and comparing the\u0000corresponding PDEs to the ABM, we demonstrate that cell aggregation and cell\u0000sorting are not possible in the PDE model. Therefore, we propose a set of\u0000stochastic mean equations (SMEs) which better capture the behaviour of the ABM\u0000in one and two dimensions.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140612262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0