arXiv - QuanBio - Cell Behavior最新文献_第5页

The morphology of cell spheroids in simple shear flow 简单剪切流中的球形细胞形态

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-11 DOI: arxiv-2404.07528

Rosalia Ferraro, Jasmin Di Franco, Sergio Caserta, Stefano Guido

{"title":"The morphology of cell spheroids in simple shear flow","authors":"Rosalia Ferraro, Jasmin Di Franco, Sergio Caserta, Stefano Guido","doi":"arxiv-2404.07528","DOIUrl":"https://doi.org/arxiv-2404.07528","url":null,"abstract":"Cell spheroids are a widely used model to investigate cell-cell and\u0000cell-matrix interactions in a 3D microenvironment in vitro. Most research on\u0000cell spheroids has been focused on their response to various stimuli under\u0000static conditions. Recently, the effect of flow on cell spheroids has been\u0000investigated in the context of tumor invasion in interstitial space. In\u0000particular, microfluidic perfusion of cell spheroids embedded in a collagen\u0000matrix has been shown to modulate cell-cell adhesion and to represent a\u0000possible mechanism promoting tumor invasion by interstitial flow. However,\u0000studies on the effects of well-defined flow fields on cell spheroids are\u0000lacking in the literature. Here, we apply simple shear flow to cell spheroids\u0000in a parallel plate apparatus while observing their morphology by optical\u0000microscopy. By using image analysis techniques, we show that cell spheroids\u0000rotate under flow as rigid particles. As time goes on, cells from the outer\u0000layer detach from the sheared cell spheroids and are carried away by the flow.\u0000Hence, the size of cell spheroids declines with time at a rate increasing with\u0000the external shear stress, which can be used to estimate cell-cell adhesion.\u0000The technique proposed in this work allows one to correlate flow-induced\u0000effects with microscopy imaging of cell spheroids in a well-established shear\u0000flow field, thus providing a method to obtain quantitative results which are\u0000relevant in the general field of mechanobiology.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575001","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

Nonlinear dynamics of confined cell migration -- modeling and inference 封闭细胞迁移的非线性动力学--建模与推理

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-10 DOI: arxiv-2404.07390

Pedrom Zadeh, Brian A. Camley

{"title":"Nonlinear dynamics of confined cell migration -- modeling and inference","authors":"Pedrom Zadeh, Brian A. Camley","doi":"arxiv-2404.07390","DOIUrl":"https://doi.org/arxiv-2404.07390","url":null,"abstract":"The motility of eukaryotic cells is strongly influenced by their environment,\u0000with confined cells often developing qualitatively different motility patterns\u0000from those migrating on simple two-dimensional substrates. Recent experiments,\u0000coupled with data-driven methods to extract a cell's equation of motion, showed\u0000that cancerous MDA-MB-231 cells persistently hop in a limit cycle when placed\u0000on two-state adhesive micropatterns (two large squares connected by a narrow\u0000bridge), while they remain stationary on average in rectangular confinements.\u0000In contrast, healthy MCF10A cells migrating on the two-state micropattern are\u0000bistable, i.e., they settle into either basin on average with only\u0000noise-induced hops between the two states. We can capture all these behaviors\u0000with a single computational phase field model of a crawling cell, under the\u0000assumption that contact with non-adhesive substrate inhibits the cell front.\u0000Our model predicts that larger and softer cells are more likely to persistently\u0000hop, while smaller and stiffer cells are more likely to be bistable. Other key\u0000factors controlling cell migration are the frequency of protrusions and their\u0000magnitude of noise. Our results show that relatively simple assumptions about\u0000how cells sense their geometry can explain a wide variety of different cell\u0000behaviors, and show the power of data-driven approaches to characterize both\u0000experiment and simulation.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140574826","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

Blood lipoproteins shape the phenotype and lipid content of early atherosclerotic lesion macrophages: a dual-structured mathematical model 血脂蛋白决定早期动脉粥样硬化病变巨噬细胞的表型和脂质含量：双结构数学模型

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-10 DOI: arxiv-2404.07051

Keith L Chambers, Mary R Myerscough, Michael G Watson, Helen M Byrne

{"title":"Blood lipoproteins shape the phenotype and lipid content of early atherosclerotic lesion macrophages: a dual-structured mathematical model","authors":"Keith L Chambers, Mary R Myerscough, Michael G Watson, Helen M Byrne","doi":"arxiv-2404.07051","DOIUrl":"https://doi.org/arxiv-2404.07051","url":null,"abstract":"Macrophages in atherosclerotic lesions exhibit a spectrum of behaviours or\u0000phenotypes. The phenotypic distribution of monocyte-derived macrophages (MDMs),\u0000its correlation with MDM lipid content, and relation to blood lipoprotein\u0000densities are not well understood. Of particular interest is the balance\u0000between low density lipoproteins (LDL) and high density lipoproteins (HDL),\u0000which carry bad and good cholesterol respectively. To address these issues, we\u0000have developed a mathematical model for early atherosclerosis in which the MDM\u0000population is structured by phenotype and lipid content. The model admits a\u0000simpler, closed subsystem whose analysis shows how lesion composition becomes\u0000more pathological as the blood density of LDL increases relative to the HDL\u0000capacity. We use asymptotic analysis to derive a power-law relationship between\u0000MDM phenotype and lipid content at steady-state. This relationship enables us\u0000to understand why, for example, lipid-laden MDMs have a more inflammatory\u0000phenotype than lipid-poor MDMs when blood LDL lipid density greatly exceeds HDL\u0000capacity. We show further that the MDM phenotype distribution always attains a\u0000local maximum, while the lipid content distribution may be unimodal, adopt a\u0000quasi-uniform profile or decrease monotonically. Pathological lesions exhibit a\u0000local maximum in both the phenotype and lipid content MDM distributions, with\u0000the maximum at an inflammatory phenotype and near the lipid content capacity\u0000respectively. These results illustrate how macrophage heterogeneity arises in\u0000early atherosclerosis and provide a framework for future model validation\u0000through comparison with single-cell RNA sequencing data.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575002","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

Does nematic order allow groups of elongated cells to sense electric fields better? 向列有序是否能让拉长的细胞群更好地感知电场？

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-06 DOI: arxiv-2404.04723

Kurmanbek Kaiyrbekov, Brian A. Camley

引用次数: 0

Emergent Simplicities in the Living Histories of Individual Cells 单个细胞生命历程中的新兴简单性

arXiv - QuanBio - Cell Behavior Pub Date : 2024-04-02 DOI: arxiv-2404.01682

Charles S. Wright, Kunaal Joshi, Rudro R. Biswas, Srividya Iyer-Biswas

{"title":"Emergent Simplicities in the Living Histories of Individual Cells","authors":"Charles S. Wright, Kunaal Joshi, Rudro R. Biswas, Srividya Iyer-Biswas","doi":"arxiv-2404.01682","DOIUrl":"https://doi.org/arxiv-2404.01682","url":null,"abstract":"Organisms maintain the status quo, holding key physiological variables\u0000constant to within an acceptable tolerance, and yet adapt with precision and\u0000plasticity to dynamic changes in externalities. What organizational principles\u0000ensure such exquisite yet robust control of systems-level \"state variables\" in\u0000complex systems with an extraordinary number of moving parts and fluctuating\u0000variables? Here we focus on these issues in the specific context of intra- and\u0000intergenerational life histories of individual bacterial cells, whose\u0000biographies are precisely charted via high-precision dynamic experiments using\u0000the SChemostat technology. We highlight intra- and intergenerational scaling\u0000laws and other \"emergent simplicities\" revealed by these high-precision data.\u0000In turn, these facilitate a principled route to dimensional reduction of the\u0000problem, and serve as essential building blocks for phenomenological and\u0000mechanistic theory. Parameter-free data-theory matches for multiple organisms\u0000validate theory frameworks, and explicate the systems physics of stochastic\u0000homeostasis and adaptation.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575007","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

Healing Regimes for Microscopic Wounds in the Vertex Model of Cell Tissues 细胞组织顶点模型中显微伤口的愈合机制

arXiv - QuanBio - Cell Behavior Pub Date : 2024-03-21 DOI: arxiv-2403.14501

R. F. Almada, N. A. M. Araujo, P. Patricio

引用次数: 0

Transfer Learning for T-Cell Response Prediction 用于 T 细胞反应预测的迁移学习

arXiv - QuanBio - Cell Behavior Pub Date : 2024-03-18 DOI: arxiv-2403.12117

Josua StadelmaierUniversity of Tübingen, Brandon MaloneNEC OncoImmunity, Ralf EggelingUniversity of Tübingen

{"title":"Transfer Learning for T-Cell Response Prediction","authors":"Josua StadelmaierUniversity of Tübingen, Brandon MaloneNEC OncoImmunity, Ralf EggelingUniversity of Tübingen","doi":"arxiv-2403.12117","DOIUrl":"https://doi.org/arxiv-2403.12117","url":null,"abstract":"We study the prediction of T-cell response for specific given peptides, which\u0000could, among other applications, be a crucial step towards the development of\u0000personalized cancer vaccines. It is a challenging task due to limited,\u0000heterogeneous training data featuring a multi-domain structure; such data\u0000entail the danger of shortcut learning, where models learn general\u0000characteristics of peptide sources, such as the source organism, rather than\u0000specific peptide characteristics associated with T-cell response. Using a transformer model for T-cell response prediction, we show that the\u0000danger of inflated predictive performance is not merely theoretical but occurs\u0000in practice. Consequently, we propose a domain-aware evaluation scheme. We then\u0000study different transfer learning techniques to deal with the multi-domain\u0000structure and shortcut learning. We demonstrate a per-source fine tuning\u0000approach to be effective across a wide range of peptide sources and further\u0000show that our final model outperforms existing state-of-the-art approaches for\u0000predicting T-cell responses for human peptides.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140165313","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

Modeling iPSC-derived Endothelial Cell Transition in Tumor Angiogenesis using Petri Nets 利用 Petri 网模拟肿瘤血管生成过程中的 iPSC 衍生内皮细胞转换

arXiv - QuanBio - Cell Behavior Pub Date : 2024-03-11 DOI: arxiv-2403.06555

Adéla Šterberová, Andreea Dincu, Stijn Oudshoorn, Vincent van Duinen, Lu Cao

{"title":"Modeling iPSC-derived Endothelial Cell Transition in Tumor Angiogenesis using Petri Nets","authors":"Adéla Šterberová, Andreea Dincu, Stijn Oudshoorn, Vincent van Duinen, Lu Cao","doi":"arxiv-2403.06555","DOIUrl":"https://doi.org/arxiv-2403.06555","url":null,"abstract":"Tumor angiogenesis concerns the development of new blood vessels supplying\u0000the necessary nutrients for the further development of existing tumor cells.\u0000The entire process is complex, involving the production and consumption of\u0000chemicals, endothelial cell transitions as well as cell interactions,\u0000divisions, and migrations. Microfluidic cell culture platform has been used to\u0000study angiogenesis of endothelial cells derived from human induced pluripotent\u0000stem cells (iPSC-ECs) for a physiological relevant micro-environment. In this\u0000paper, we elaborate on how to define a pipeline for simulating the\u0000transformation and process that an iPSC-derived endothelial cell goes through\u0000in this biological scenario. We leverage the robustness and simplicity of Petri\u0000nets for modeling the cell transformation and associated constraints. The\u0000environmental and spacial factors are added using custom 2-dimensional grids.\u0000Although the pipeline does not capture the entire complexity of tumor\u0000angiogenesis, we are able to capture the essence of endothelial cell\u0000transitions in tumor angiogenesis using this conceptually simplified solution.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140107078","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

Properties of Hagen-Poiseuille flows in channel networks 渠道网络中哈根-普瓦耶流的特性

arXiv - QuanBio - Cell Behavior Pub Date : 2024-02-29 DOI: arxiv-2402.19185

A. F. Valente, R. Almeida, R. Dilão

引用次数: 0

Why Attention Graphs Are All We Need: Pioneering Hierarchical Classification of Hematologic Cell Populations with LeukoGraph 为什么我们只需要注意图？利用 LeukoGraph 率先对血液细胞群进行分级分类

arXiv - QuanBio - Cell Behavior Pub Date : 2024-02-28 DOI: arxiv-2402.18610

Fatemeh Nassajian Mojarrad, Lorenzo Bini, Thomas Matthes, Stéphane Marchand-Maillet

{"title":"Why Attention Graphs Are All We Need: Pioneering Hierarchical Classification of Hematologic Cell Populations with LeukoGraph","authors":"Fatemeh Nassajian Mojarrad, Lorenzo Bini, Thomas Matthes, Stéphane Marchand-Maillet","doi":"arxiv-2402.18610","DOIUrl":"https://doi.org/arxiv-2402.18610","url":null,"abstract":"In the complex landscape of hematologic samples such as peripheral blood or\u0000bone marrow, cell classification, delineating diverse populations into a\u0000hierarchical structure, presents profound challenges. This study presents\u0000LeukoGraph, a recently developed framework designed explicitly for this purpose\u0000employing graph attention networks (GATs) to navigate hierarchical\u0000classification (HC) complexities. Notably, LeukoGraph stands as a pioneering\u0000effort, marking the application of graph neural networks (GNNs) for\u0000hierarchical inference on graphs, accommodating up to one million nodes and\u0000millions of edges, all derived from flow cytometry data. LeukoGraph intricately\u0000addresses a classification paradigm where for example four different cell\u0000populations undergo flat categorization, while a fifth diverges into two\u0000distinct child branches, exemplifying the nuanced hierarchical structure\u0000inherent in complex datasets. The technique is more general than this example.\u0000A hallmark achievement of LeukoGraph is its F-score of 98%, significantly\u0000outclassing prevailing state-of-the-art methodologies. Crucially, LeukoGraph's\u0000prowess extends beyond theoretical innovation, showcasing remarkable precision\u0000in predicting both flat and hierarchical cell types across flow cytometry\u0000datasets from 30 distinct patients. This precision is further underscored by\u0000LeukoGraph's ability to maintain a correct label ratio, despite the inherent\u0000challenges posed by hierarchical classifications.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140003616","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