arXiv - QuanBio - Cell Behavior最新文献_第10页

Using a probabilistic approach to derive a two-phase model of flow-induced cell migration 利用概率方法推导了细胞流动诱导迁移的两相模型

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-25 DOI: arxiv-2309.13982

Yaron Ben-Ami, Joe M. Pitt-Francis, Philip K. Maini, Helen M. Byrne

{"title":"Using a probabilistic approach to derive a two-phase model of flow-induced cell migration","authors":"Yaron Ben-Ami, Joe M. Pitt-Francis, Philip K. Maini, Helen M. Byrne","doi":"arxiv-2309.13982","DOIUrl":"https://doi.org/arxiv-2309.13982","url":null,"abstract":"Interstitial fluid flow is a feature of many solid tumours. In vitro\u0000experiments have shown that such fluid flow can direct tumour cell movement\u0000upstream or downstream depending on the balance between the competing\u0000mechanisms of tensotaxis and autologous chemotaxis. In this work we develop a\u0000probabilistic-continuum, two-phase model for cell migration in response to\u0000interstitial flow. We use a Fokker-Planck type equation for the cell-velocity\u0000probability density function, and model the flow-dependent mechanochemical\u0000stimulus as a forcing term which biases cell migration upstream and downstream.\u0000Using velocity-space averaging, we reformulate the model as a system of\u0000continuum equations for the spatio-temporal evolution of the cell volume\u0000fraction and flux, in response to forcing terms which depend on the local\u0000direction and magnitude of the mechanochemical cues. We specialise our model to\u0000describe a one-dimensional cell layer subject to fluid flow. Using a\u0000combination of numerical simulations and asymptotic analysis, we delineate the\u0000parameter regime where transitions from downstream to upstream cell migration\u0000occur. As has been observed experimentally, the model predicts\u0000downstream-oriented, chemotactic migration at low cell volume fractions, and\u0000upstream-oriented, tensotactic migration at larger volume fractions. We show\u0000that the locus of the critical volume fraction, at which the system transitions\u0000from downstream to upstream migration, is dominated by the ratio of the rate of\u0000chemokine secretion and advection. Our model predicts that, because the\u0000tensotactic stimulus depends strongly on the cell volume fraction, upstream\u0000migration occurs only transiently when the cells are initially seeded, and\u0000transitions to downstream migration occur at later times due to the dispersive\u0000effect of cell diffusion.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"23 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138523140","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

The role of the nucleus for cell mechanics: an elastic phase field approach 细胞核在细胞力学中的作用:弹性相场方法

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-22 DOI: arxiv-2309.12777

Robert Chojowski, Ulrich S. Schwarz, Falko Ziebert

引用次数: 0

Improved Breast Cancer Diagnosis through Transfer Learning on Hematoxylin and Eosin Stained Histology Images 苏木精和伊红染色组织学图像迁移学习提高乳腺癌诊断

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-15 DOI: arxiv-2309.08745

Fahad Ahmed, Reem Abdel-Salam, Leon Hamnett, Mary Adewunmi, Temitope Ayano

{"title":"Improved Breast Cancer Diagnosis through Transfer Learning on Hematoxylin and Eosin Stained Histology Images","authors":"Fahad Ahmed, Reem Abdel-Salam, Leon Hamnett, Mary Adewunmi, Temitope Ayano","doi":"arxiv-2309.08745","DOIUrl":"https://doi.org/arxiv-2309.08745","url":null,"abstract":"Breast cancer is one of the leading causes of death for women worldwide.\u0000Early screening is essential for early identification, but the chance of\u0000survival declines as the cancer progresses into advanced stages. For this\u0000study, the most recent BRACS dataset of histological (H&E) stained images was\u0000used to classify breast cancer tumours, which contains both the whole-slide\u0000images (WSI) and region-of-interest (ROI) images, however, for our study we\u0000have considered ROI images. We have experimented using different pre-trained\u0000deep learning models, such as Xception, EfficientNet, ResNet50, and\u0000InceptionResNet, pre-trained on the ImageNet weights. We pre-processed the\u0000BRACS ROI along with image augmentation, upsampling, and dataset split\u0000strategies. For the default dataset split, the best results were obtained by\u0000ResNet50 achieving 66% f1-score. For the custom dataset split, the best\u0000results were obtained by performing upsampling and image augmentation which\u0000results in 96.2% f1-score. Our second approach also reduced the number of\u0000false positive and false negative classifications to less than 3% for each\u0000class. We believe that our study significantly impacts the early diagnosis and\u0000identification of breast cancer tumors and their subtypes, especially atypical\u0000and malignant tumors, thus improving patient outcomes and reducing patient\u0000mortality rates. Overall, this study has primarily focused on identifying seven\u0000(7) breast cancer tumor subtypes, and we believe that the experimental models\u0000can be fine-tuned further to generalize over previous breast cancer histology\u0000datasets as well.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522603","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

Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis 基于知识图的定向散射蜂窝信号分析

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-14 DOI: arxiv-2309.07813

Aarthi Venkat, Joyce Chew, Ferran Cardoso Rodriguez, Christopher J. Tape, Michael Perlmutter, Smita Krishnaswamy

{"title":"Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis","authors":"Aarthi Venkat, Joyce Chew, Ferran Cardoso Rodriguez, Christopher J. Tape, Michael Perlmutter, Smita Krishnaswamy","doi":"arxiv-2309.07813","DOIUrl":"https://doi.org/arxiv-2309.07813","url":null,"abstract":"Directed graphs are a natural model for many phenomena, in particular\u0000scientific knowledge graphs such as molecular interaction or chemical reaction\u0000networks that define cellular signaling relationships. In these situations,\u0000source nodes typically have distinct biophysical properties from sinks. Due to\u0000their ordered and unidirectional relationships, many such networks also have\u0000hierarchical and multiscale structure. However, the majority of methods\u0000performing node- and edge-level tasks in machine learning do not take these\u0000properties into account, and thus have not been leveraged effectively for\u0000scientific tasks such as cellular signaling network inference. We propose a new\u0000framework called Directed Scattering Autoencoder (DSAE) which uses a directed\u0000version of a geometric scattering transform, combined with the non-linear\u0000dimensionality reduction properties of an autoencoder and the geometric\u0000properties of the hyperbolic space to learn latent hierarchies. We show this\u0000method outperforms numerous others on tasks such as embedding directed graphs\u0000and learning cellular signaling networks.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138523142","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

Regulation of store-operated calcium entry 储运钙进入的调控

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-13 DOI: arxiv-2309.06907

Goutham Kodakandla, Askar Akimzhanov, Darren Boehning

{"title":"Regulation of store-operated calcium entry","authors":"Goutham Kodakandla, Askar Akimzhanov, Darren Boehning","doi":"arxiv-2309.06907","DOIUrl":"https://doi.org/arxiv-2309.06907","url":null,"abstract":"Plasma membrane calcium influx through ion channels is crucial for many\u0000events in cellular physiology. Cell surface stimuli lead to the production of\u0000inositol 1,4,5-trisphosphate (IP3), which binds to IP3 receptors in the\u0000endoplasmic reticulum (ER) to release calcium pools from the ER lumen. This\u0000leads to depletion of ER calcium pools which has been termed store-depletion.\u0000Store-depletion leads the dissociation of calcium ions from the EF-hand motif\u0000of the ER calcium sensor Stromal Interaction Molecule 1 (STIM1). This leads to\u0000a conformational change in STIM1 which helps it to interact with a plasma\u0000membrane (PM) at ER:PM junctions. At these ER:PM junctions, STIM1 binds to and\u0000activates a calcium channel known as Orai1 to form calcium-release activated\u0000calcium (CRAC) channels. Activation of Orai1 leads to calcium influx, known as\u0000store-operated calcium entry (SOCE). In addition to Orai1 and STIM1, the\u0000homologs of Orai1 and STIM1, such as Orai2/3 and STIM2 also play a crucial role\u0000in calcium homeostasis. The influx of calcium through the Orai channel\u0000activates a calcium current that has been termed CRAC currents. CRAC channels\u0000form multimers and cluster together in large macromolecular assemblies termed\u0000puncta. How these CRAC channels form puncta has been contentious since their\u0000discovery. In this review, we will outline the history of SOCE, the molecular\u0000players involved in this process (Orai and STIM proteins, TRP channels,\u0000SOCE-associated regulatory factor etc.), as well as the models that have been\u0000proposed to explain this important mechanism in cellular physiology.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522604","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

Dynamics of cell-type transition mediated by epigenetic modifications 表观遗传修饰介导的细胞型转换动力学

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-13 DOI: arxiv-2309.07356

Rongsheng Huang, Qiaojun Situ, Jinzhi Lei

{"title":"Dynamics of cell-type transition mediated by epigenetic modifications","authors":"Rongsheng Huang, Qiaojun Situ, Jinzhi Lei","doi":"arxiv-2309.07356","DOIUrl":"https://doi.org/arxiv-2309.07356","url":null,"abstract":"Maintaining tissue homeostasis requires appropriate regulation of stem cell\u0000differentiation. The Waddington landscape posits that gene circuits in a cell\u0000form a potential landscape of different cell types, wherein cells follow\u0000attractors of the probability landscape to develop into distinct cell types.\u0000However, how adult stem cells achieve a delicate balance between self-renewal\u0000and differentiation remains unclear. We propose that random inheritance of\u0000epigenetic states plays a pivotal role in stem cell differentiation and present\u0000a hybrid model of stem cell differentiation induced by epigenetic\u0000modifications. Our comprehensive model integrates gene regulation networks,\u0000epigenetic state inheritance, and cell regeneration, encompassing multi-scale\u0000dynamics ranging from transcription regulation to cell population. Through\u0000model simulations, we demonstrate that random inheritance of epigenetic states\u0000during cell divisions can spontaneously induce cell differentiation,\u0000dedifferentiation, and transdifferentiation. Furthermore, we investigate the\u0000influences of interfering with epigenetic modifications and introducing\u0000additional transcription factors on the probabilities of dedifferentiation and\u0000transdifferentiation, revealing the underlying mechanism of cell reprogramming.\u0000This textit{in silico} model provides valuable insights into the intricate\u0000mechanism governing stem cell differentiation and cell reprogramming and offers\u0000a promising path to enhance the field of regenerative medicine.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"213 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522679","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

A dynamic fluid landscape mediates the spread of bacteria 动态的流体景观有助于细菌的传播

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-11 DOI: arxiv-2309.05351

Divakar Badal, Aloke Kumar, Varsha Singh, Danny Raj M

{"title":"A dynamic fluid landscape mediates the spread of bacteria","authors":"Divakar Badal, Aloke Kumar, Varsha Singh, Danny Raj M","doi":"arxiv-2309.05351","DOIUrl":"https://doi.org/arxiv-2309.05351","url":null,"abstract":"Microbial interactions regulate their spread and survival in competitive\u0000environments. It is not clear if the physical parameters of the environment\u0000regulate the outcome of these interactions. In this work, we show that the\u0000opportunistic pathogen Pseudomonas aeruginosa occupies a larger area on the\u0000substratum in the presence of yeast such as Cryptococcus neoformans , than\u0000without it. At the microscopic level, bacterial cells show an enhanced activity\u0000in the vicinity of yeast cells. We observe this behaviour even when the live\u0000yeast cells are replaced with heat-killed cells or with spherical glass beads\u0000of similar morphology, which suggests that the observed behaviour is not\u0000specific to the biology of microbes. Upon careful investigation, we find that a\u0000fluid pool is formed around yeast cells which facilitates the swimming of the\u0000flagellated P. aeruginosa , causing their enhanced motility. Using mathematical\u0000modeling we demonstrate how this local enhancement of bacterial motility leads\u0000to the enhanced spread observed at the level of the plate. We find that the\u0000dynamics of the fluid landscape around the bacteria, mediated by the growing\u0000yeast lawn, affects the spreading. For instance, when the yeast lawn grows\u0000faster, a bacterial colony prefers a lower initial loading of yeast cells for\u0000optimum enhancement in the spread. We confirm our predictions using Candida\u0000albicans and C. neoformans, at different initial compositions. In summary, our\u0000work shows the importance of considering the dynamically changing physical\u0000environment while studying bacterial motility in complex environments.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522608","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

Numerical reconstruction of the kinetic chemotaxis kernel from macroscopic measurement, wellposedness and illposedness 动力学趋化核的宏观测量、适态性和病态性的数值重建

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-10 DOI: arxiv-2309.05004

Kathrin Hellmuth, Christian Klingenberg, Qin Li, Min Tang

引用次数: 0

Parameter identifiability and model selection for partial differential equation models of cell invasion 细胞侵袭偏微分方程模型的参数可辨识性及模型选择

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-04 DOI: arxiv-2309.01476

Yue LiuMathematical Institute, University of Oxford, Kevin SuhDepartment of Chemical and Biological Engineering, Princeton University, Philip K. MainiMathematical Institute, University of Oxford, Daniel J. CohenDepartment of Chemical and Biological Engineering, Princeton UniversityDepartment of Mechanical and Aerospace Engineering, Princeton University, Ruth E. BakerMathematical Institute, University of Oxford

{"title":"Parameter identifiability and model selection for partial differential equation models of cell invasion","authors":"Yue LiuMathematical Institute, University of Oxford, Kevin SuhDepartment of Chemical and Biological Engineering, Princeton University, Philip K. MainiMathematical Institute, University of Oxford, Daniel J. CohenDepartment of Chemical and Biological Engineering, Princeton UniversityDepartment of Mechanical and Aerospace Engineering, Princeton University, Ruth E. BakerMathematical Institute, University of Oxford","doi":"arxiv-2309.01476","DOIUrl":"https://doi.org/arxiv-2309.01476","url":null,"abstract":"When employing a mechanistic model to study biological systems, practical\u0000parameter identifiability is important for making predictions in a wide range\u0000of scenarios, as well as for understanding the mechanisms driving the system\u0000behaviour. We argue that parameter identifiability should be considered\u0000alongside goodness-of-fit and model complexity as criteria for model selection.\u0000To demonstrate, we use a profile likelihood approach to investigate parameter\u0000identifiability for four extensions of the Fisher--KPP model, given\u0000experimental data from a cell invasion assay. We show that more complicated\u0000models tend to be less identifiable, with parameter estimates being more\u0000sensitive to subtle differences in experimental procedures, and require more\u0000data to be practically identifiable. The results from identifiability analysis\u0000can inform model selection, as well as data collection and experimental design.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"35 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522605","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

Learning dynamical models of single and collective cell migration: a review 学习单个和集体细胞迁移的动态模型:综述

arXiv - QuanBio - Cell Behavior Pub Date : 2023-09-01 DOI: arxiv-2309.00545

David B. Brückner, Chase P. Broedersz

{"title":"Learning dynamical models of single and collective cell migration: a review","authors":"David B. Brückner, Chase P. Broedersz","doi":"arxiv-2309.00545","DOIUrl":"https://doi.org/arxiv-2309.00545","url":null,"abstract":"Single and collective cell migration are fundamental processes critical for\u0000physiological phenomena ranging from embryonic development and immune response\u0000to wound healing and cancer metastasis. To understand cell migration from a\u0000physical perspective, a broad variety of models for the underlying physical\u0000mechanisms that govern cell motility have been developed. A key challenge in\u0000the development of such models is how to connect them to experimental\u0000observations, which often exhibit complex stochastic behaviours. In this\u0000review, we discuss recent advances in data-driven theoretical approaches that\u0000directly connect with experimental data to infer dynamical models of stochastic\u0000cell migration. Leveraging advances in nanofabrication, image analysis, and\u0000tracking technology, experimental studies now provide unprecedented large\u0000datasets on cellular dynamics. In parallel, theoretical efforts have been\u0000directed towards integrating such datasets into physical models from the single\u0000cell to the tissue scale with the aim of conceptualizing the emergent behavior\u0000of cells. We first review how this inference problem has been addressed in\u0000freely migrating cells on two-dimensional substrates and in structured,\u0000confining systems. Moreover, we discuss how data-driven methods can be\u0000connected with molecular mechanisms, either by integrating mechanistic\u0000bottom-up biophysical models, or by performing inference on subcellular degrees\u0000of freedom. Finally, we provide an overview of applications of data-driven\u0000modelling in developing frameworks for cell-to-cell variability in behaviours,\u0000and for learning the collective dynamics of multicellular systems.\u0000Specifically, we review inference and machine learning approaches to recover\u0000cell-cell interactions and collective dynamical modes, and how these can be\u0000integrated into physical active matter models of collective migration.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":"26 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138522607","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