Pub Date : 2024-10-22DOI: 10.1016/j.jtbi.2024.111965
Gordon R. McNicol , Matthew J. Dalby , Peter S. Stewart
To function and survive cells need to be able to sense and respond to their local environment through mechanotransduction. Crucially, mechanical and biochemical perturbations initiate cell signalling cascades, which can induce responses such as growth, apoptosis, proliferation and differentiation. At the heart of this process are actomyosin stress fibres (SFs), which form part of the cell cytoskeleton, and focal adhesions (FAs), which bind this cytoskeleton to the extra-cellular matrix (ECM). The formation and maturation of these structures (connected by a positive feedback loop) is pivotal in non-motile cells, where SFs are generally of ventral type, interconnecting FAs and producing isometric tension. In this study we formulate a one-dimensional bio-chemo-mechanical continuum model to describe the coupled formation and maturation of ventral SFs and FAs. We use a set of reaction–diffusion–advection equations to describe three sets of biochemical events: the polymerisation of actin and subsequent bundling into activated SFs; the formation and maturation of cell–substrate adhesions; and the activation of signalling proteins in response to FA and SF formation. The evolution of these key proteins is coupled to a Kelvin–Voigt viscoelastic description of the cell cytoplasm and the ECM. We employ this model to understand how cells respond to external and intracellular cues in vitro and are able to reproduce experimentally observed phenomena including non-uniform cell striation and cells forming weaker SFs and FAs on softer substrates.
细胞要发挥功能并存活下来，就必须能够通过机械传导来感知和响应局部环境。至关重要的是，机械和生化扰动会启动细胞信号级联，从而诱发生长、凋亡、增殖和分化等反应。这一过程的核心是构成细胞细胞骨架的肌动蛋白应力纤维（SF）和将细胞骨架与细胞外基质（ECM）结合在一起的病灶粘附（FA）。在非运动细胞中，这些结构（通过正反馈回路连接）的形成和成熟至关重要，其中 SF 通常为腹侧型，与 FA 相互连接并产生等距张力。在这项研究中，我们建立了一个一维生物化学-机械连续模型来描述腹侧 SFs 和 FAs 的耦合形成和成熟。我们使用一组反应-扩散-平流方程来描述三组生化事件：肌动蛋白的聚合和随后捆绑成活化的 SFs；细胞-基质粘附的形成和成熟；以及信号蛋白对 FA 和 SF 形成的激活反应。这些关键蛋白的进化与细胞胞质和 ECM 的开尔文-沃依格粘弹性描述相关联。我们利用这一模型来了解细胞如何在体外对外界和细胞内的线索做出反应，并能重现实验观察到的现象，包括细胞条纹不均匀以及细胞在较软的基质上形成较弱的 SF 和 FA。
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Pub Date : 2024-10-22DOI: 10.1016/j.jtbi.2024.111971
Min Wu
Growth-elasticity (also known as morphoelasticity) is a powerful model framework for understanding complex shape development in soft biological tissues. At each instant, by mapping how continuum building blocks have grown geometrically and how they respond elastically to the push-and-pull from their neighbors, the shape of the growing structure is determined from a state of mechanical equilibrium. As mechanical loads continue to be added to the system through growth, many interesting shapes, such as smooth wavy wrinkles, sharp creases, and deep folds, can form on the tissue surface from a relatively flatter geometry.
Previous numerical simulations of growth-elasticity have reproduced many interesting shapes resembling those observed in reality, such as the foldings on mammalian brains and guts. In the case of mammalian guts, it has been shown that wavy wrinkles, deep folds, and sharp creases on the interior organ surface can be simulated even under a simple assumption of isotropic uniform growth in the interior layer of the organ. Interestingly, the simulated patterns are all regular along the tube’s circumference, with either all smooth or all sharp indentations, whereas some undulation patterns in reality exhibit irregular patterns and a mixture of sharp creases and smooth indentations along the circumference. Can we simulate irregular indentation patterns without further complicating the growth patterning?
In this paper, we have discovered abundant shape solutions with irregular indentation patterns by developing a Rayleigh–Ritz finite-element method (FEM). In contrast to previous Galerkin FEMs, which solve the weak formulation of the mechanical-equilibrium equations, the new method formulates an optimization problem for the discretized energy functional, whose critical points are equivalent to solutions obtained by solving the mechanical-equilibrium equations. This new method is more robust than previous methods. Specifically, it does not require the initial guess to be near a solution to achieve convergence, and it allows control over the direction of numerical iterates across the energy landscape. This approach enables the capture of more solutions that cannot be easily reached by previous methods. In addition to the previously found regular smooth and non-smooth configurations, we have identified a new transitional irregular smooth shape, new shapes with a mixture of smooth and non-smooth surface indentations, and a variety of irregular patterns with different numbers of creases. Our numerical results demonstrate that growth-elasticity modeling can match more shape patterns observed in reality than previously thought.
{"title":"Simulating irregular symmetry breaking in gut cross sections using a novel energy-optimization approach in growth-elasticity","authors":"Min Wu","doi":"10.1016/j.jtbi.2024.111971","DOIUrl":"10.1016/j.jtbi.2024.111971","url":null,"abstract":"<div><div>Growth-elasticity (also known as morphoelasticity) is a powerful model framework for understanding complex shape development in soft biological tissues. At each instant, by mapping how continuum building blocks have grown geometrically and how they respond elastically to the push-and-pull from their neighbors, the shape of the growing structure is determined from a state of mechanical equilibrium. As mechanical loads continue to be added to the system through growth, many interesting shapes, such as smooth wavy wrinkles, sharp creases, and deep folds, can form on the tissue surface from a relatively flatter geometry.</div><div>Previous numerical simulations of growth-elasticity have reproduced many interesting shapes resembling those observed in reality, such as the foldings on mammalian brains and guts. In the case of mammalian guts, it has been shown that wavy wrinkles, deep folds, and sharp creases on the interior organ surface can be simulated even under a simple assumption of isotropic uniform growth in the interior layer of the organ. Interestingly, the simulated patterns are all regular along the tube’s circumference, with either all smooth or all sharp indentations, whereas some undulation patterns in reality exhibit irregular patterns and a mixture of sharp creases and smooth indentations along the circumference. Can we simulate irregular indentation patterns without further complicating the growth patterning?</div><div>In this paper, we have discovered abundant shape solutions with irregular indentation patterns by developing a Rayleigh–Ritz finite-element method (FEM). In contrast to previous Galerkin FEMs, which solve the weak formulation of the mechanical-equilibrium equations, the new method formulates an optimization problem for the discretized energy functional, whose critical points are equivalent to solutions obtained by solving the mechanical-equilibrium equations. This new method is more robust than previous methods. Specifically, it does not require the initial guess to be near a solution to achieve convergence, and it allows control over the direction of numerical iterates across the energy landscape. This approach enables the capture of more solutions that cannot be easily reached by previous methods. In addition to the previously found regular smooth and non-smooth configurations, we have identified a new transitional irregular smooth shape, new shapes with a mixture of smooth and non-smooth surface indentations, and a variety of irregular patterns with different numbers of creases. Our numerical results demonstrate that growth-elasticity modeling can match more shape patterns observed in reality than previously thought.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111971"},"PeriodicalIF":1.9,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.jtbi.2024.111973
Eileen Joan Magero , Koichi Unami , Osama Mohawesh , Marie Sato
We develop and analyze a temporally continuous spatially lumped resource budget model to explain the dynamics of synchronized biennial-bearing olives in the Levant, specifically focusing on Syria, the region’s foremost olive-producing country. The model is a time-continuous counterpart of the celebrated resource budget model. It consists of a Duffing oscillator coupled with a dynamical model of pollination with an external force propelling olive growth by photosynthesis. The reference data are obtained from statistical databases of international organizations and our own observation systems in Jordan, a country neighboring Syria, providing a wealth of information to refine the model structure. An intensive review of Syria’s modern history involving significant shifts in agricultural policy and social stability leads to a conclusion that the model should comprehend the anomaly of olive yield interacting with socio-political factors as an autonomous behavior. The conventional mathematical methodology analyzes the model’s characteristics, such as solutions’ non-negativity, boundedness, and stability. The system is stable during pollination off-season but may become unstable and unbounded during pollination on-season, which is a property that the time-discrete resource budget model cannot reproduce. A significant finding is that coupling individual fruit trees by anemophily is not essential in synchronization, overturning earlier studies in the literature. The values of model parameters that best fit the historical data of olive yield in Syria result in bounded chaos. With alternative parameter values, the model could exhibit periodic oscillation, instability, or blowing up, as clearly shown in bifurcation diagrams.
{"title":"Resource budget model with Duffing oscillator for dynamics of synchronized biennial-bearing olives in the Levant","authors":"Eileen Joan Magero , Koichi Unami , Osama Mohawesh , Marie Sato","doi":"10.1016/j.jtbi.2024.111973","DOIUrl":"10.1016/j.jtbi.2024.111973","url":null,"abstract":"<div><div>We develop and analyze a temporally continuous spatially lumped resource budget model to explain the dynamics of synchronized biennial-bearing olives in the Levant, specifically focusing on Syria, the region’s foremost olive-producing country. The model is a time-continuous counterpart of the celebrated resource budget model. It consists of a Duffing oscillator coupled with a dynamical model of pollination with an external force propelling olive growth by photosynthesis. The reference data are obtained from statistical databases of international organizations and our own observation systems in Jordan, a country neighboring Syria, providing a wealth of information to refine the model structure. An intensive review of Syria’s modern history involving significant shifts in agricultural policy and social stability leads to a conclusion that the model should comprehend the anomaly of olive yield interacting with socio-political factors as an autonomous behavior. The conventional mathematical methodology analyzes the model’s characteristics, such as solutions’ non-negativity, boundedness, and stability. The system is stable during pollination off-season but may become unstable and unbounded during pollination on-season, which is a property that the time-discrete resource budget model cannot reproduce. A significant finding is that coupling individual fruit trees by anemophily is not essential in synchronization, overturning earlier studies in the literature. The values of model parameters that best fit the historical data of olive yield in Syria result in bounded chaos. With alternative parameter values, the model could exhibit periodic oscillation, instability, or blowing up, as clearly shown in bifurcation diagrams.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111973"},"PeriodicalIF":1.9,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.jtbi.2024.111972
Stephanie Young , Jérôme Gilles
A 3D chaos game is shown to be a useful way for encoding DNA sequences. Since matching subsequences in DNA converge in space in 3D chaos game encoding, a DNA sequence’s 3D chaos game representation can be used to compare DNA sequences without prior alignment and without truncating or padding any of the sequences. Two proposed methods inspired by shape-similarity comparison techniques show that this form of encoding can perform as well as alignment-based techniques for building phylogenetic trees. The first method uses the volume overlap of intersecting spheres and the second uses shape signatures by summarizing the coordinates, oriented angles, and oriented distances of the 3D chaos game trajectory. The methods are tested using: (1) the first exon of the beta-globin gene for 11 species, (2) mitochondrial DNA from four groups of primates, and (3) a set of synthetic DNA sequences. Simulations show that the proposed methods produce distances that reflect the number of mutation events; additionally, on average, distances resulting from deletion mutations are comparable to those produced by substitution mutations.
三维混沌游戏是对 DNA 序列进行编码的有效方法。由于在三维混沌游戏编码中，DNA 中的匹配子序列在空间上趋同，DNA 序列的三维混沌游戏表示法可用于比较 DNA 序列，而无需事先进行比对，也无需截断或填充任何序列。受形状相似性比较技术启发而提出的两种方法表明，这种编码方式在构建系统发生树方面与基于比对的技术一样出色。第一种方法使用相交球体的体积重叠，第二种方法通过总结三维混沌游戏轨迹的坐标、定向角和定向距离来使用形状特征。对这些方法进行了测试：(1) 11 个物种的β-球蛋白基因的第一个外显子；(2) 四组灵长类动物的线粒体 DNA；(3) 一组合成 DNA 序列。模拟结果表明，所提出的方法产生的距离能够反映突变事件的数量；此外，平均而言，缺失突变产生的距离与置换突变产生的距离相当。
{"title":"Use of 3D chaos game representation to quantify DNA sequence similarity with applications for hierarchical clustering","authors":"Stephanie Young , Jérôme Gilles","doi":"10.1016/j.jtbi.2024.111972","DOIUrl":"10.1016/j.jtbi.2024.111972","url":null,"abstract":"<div><div>A 3D chaos game is shown to be a useful way for encoding DNA sequences. Since matching subsequences in DNA converge in space in 3D chaos game encoding, a DNA sequence’s 3D chaos game representation can be used to compare DNA sequences without prior alignment and without truncating or padding any of the sequences. Two proposed methods inspired by shape-similarity comparison techniques show that this form of encoding can perform as well as alignment-based techniques for building phylogenetic trees. The first method uses the volume overlap of intersecting spheres and the second uses shape signatures by summarizing the coordinates, oriented angles, and oriented distances of the 3D chaos game trajectory. The methods are tested using: (1) the first exon of the beta-globin gene for 11 species, (2) mitochondrial DNA from four groups of primates, and (3) a set of synthetic DNA sequences. Simulations show that the proposed methods produce distances that reflect the number of mutation events; additionally, on average, distances resulting from deletion mutations are comparable to those produced by substitution mutations.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"596 ","pages":"Article 111972"},"PeriodicalIF":1.9,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.jtbi.2024.111970
V. Volpert
The intricate interplay between the state and society may foster opposition and prompt collective action as a mode of protest. When the state responds repressively to such collective action, it aims to undermine it escalating its costs. A mathematical model relating the repressive response to collective action, articulated through differential equations, facilitates a thorough analysis of their dynamic interaction. Modelling outcomes indicate that repressive regimes may exhibit sustained persistence, oscillatory patterns, or destabilization, potentially transitioning into alternative regimes. This modelling framework offers a means to discern the impact of diverse factors on the dynamics of repressive regimes and to provide modelling insight on the emergence of cycles of protest observed in different countries during certain periods of their history.
{"title":"Mathematical model of repressive response to collective action and protest waves","authors":"V. Volpert","doi":"10.1016/j.jtbi.2024.111970","DOIUrl":"10.1016/j.jtbi.2024.111970","url":null,"abstract":"<div><div>The intricate interplay between the state and society may foster opposition and prompt collective action as a mode of protest. When the state responds repressively to such collective action, it aims to undermine it escalating its costs. A mathematical model relating the repressive response to collective action, articulated through differential equations, facilitates a thorough analysis of their dynamic interaction. Modelling outcomes indicate that repressive regimes may exhibit sustained persistence, oscillatory patterns, or destabilization, potentially transitioning into alternative regimes. This modelling framework offers a means to discern the impact of diverse factors on the dynamics of repressive regimes and to provide modelling insight on the emergence of cycles of protest observed in different countries during certain periods of their history.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111970"},"PeriodicalIF":1.9,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-18DOI: 10.1016/j.jtbi.2024.111969
Marcus Baaz , Tim Cardilin , Torbjörn Lundh , Mats Jirstrand
A large enough sample size of patients is required to statistically show that one treatment is better than another. However, too large a sample size is expensive and can also result in findings that are statistically significant, but not clinically relevant. How sample sizes should be chosen is a well-studied problem in classical statistics and analytical expressions can be derived from the appropriate test statistic. However, these expressions require information regarding the efficacy of the treatment, which may not be available, particularly for newly developed drugs. Tumor growth inhibition (TGI) models are frequently used to quantify the efficacy of newly developed anticancer drugs. In these models, the tumor growth dynamics are commonly described by a set of ordinary differential equations containing parameters that must be estimated using experimental data.
One widely used endpoint in clinical trials is the proportion of patients in different response categories determined using the Response Evaluation Criteria In Solid Tumors (RECIST) framework. From the TGI model, we derive analytical expressions for the probability of patient response to combination therapy. The probabilistic expressions are used together with classical statistics to derive a parametric model for the sample size required to achieve a certain significance level and test power when comparing two treatments.
Furthermore, the probabilistic expressions are used to generalize the Tumor Static Exposure concept to be more suitable for predicting clinical response. The derivatives of the probabilistic expressions are used to derive two additional expressions characterizing the exposure and its sensitivity. Finally, our results are illustrated using parameters obtained from calibrating the model to preclinical data.
{"title":"Probabilistic analysis of tumor growth inhibition models to Support trial design","authors":"Marcus Baaz , Tim Cardilin , Torbjörn Lundh , Mats Jirstrand","doi":"10.1016/j.jtbi.2024.111969","DOIUrl":"10.1016/j.jtbi.2024.111969","url":null,"abstract":"<div><div>A large enough sample size of patients is required to statistically show that one treatment is better than another. However, too large a sample size is expensive and can also result in findings that are statistically significant, but not clinically relevant. How sample sizes should be chosen is a well-studied problem in classical statistics and analytical expressions can be derived from the appropriate test statistic. However, these expressions require information regarding the efficacy of the treatment, which may not be available, particularly for newly developed drugs. Tumor growth inhibition (TGI) models are frequently used to quantify the efficacy of newly developed anticancer drugs. In these models, the tumor growth dynamics are commonly described by a set of ordinary differential equations containing parameters that must be estimated using experimental data.</div><div>One widely used endpoint in clinical trials is the proportion of patients in different response categories determined using the Response Evaluation Criteria In Solid Tumors (RECIST) framework. From the TGI model, we derive analytical expressions for the probability of patient response to combination therapy. The probabilistic expressions are used together with classical statistics to derive a parametric model for the sample size required to achieve a certain significance level and test power when comparing two treatments.</div><div>Furthermore, the probabilistic expressions are used to generalize the Tumor Static Exposure concept to be more suitable for predicting clinical response. The derivatives of the probabilistic expressions are used to derive two additional expressions characterizing the exposure and its sensitivity. Finally, our results are illustrated using parameters obtained from calibrating the model to preclinical data.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111969"},"PeriodicalIF":1.9,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, we present a mechanobiochemical model for two-dimensional cell migration which couples mechanical properties of the cell cytosol with biochemical processes taking place near or on the cell plasma membrane. The modelling approach is based on a recently developed mathematical formalism of evolving bulk-surface partial differential equations of reaction–diffusion type. We solve these equations using finite element methods within a moving-mesh framework derived from the weak formulation of the evolving bulk-surface PDEs. In the present work, the cell cytosol interior (bulk) dynamics are coupled to the cell membrane (surface) dynamics through non-homogeneous Dirichlet boundary conditions. The modelling approach exhibits both directed cell migration in response to chemical cues as well as spontaneous migration in the absence of such cues. As a by-product, the approach shows fundamental characteristics associated with single cell migration such as: (i) cytosolic and membrane polarisation, (ii) actin dependent protrusions, and (iii) continuous shape deformation of the cell during migration.
Cell migration is an ubiquitous process in life that is mainly triggered by the dynamics of the actin cytoskeleton and therefore is driven by both mechanical and biochemical processes. It is a multistep process essential for mammalian organisms and is closely linked to a vast diversity of processes; from embryonic development to cancer invasion. Experimental, theoretical and computational studies have been key to elucidate the mechanisms underlying cell migration. On one hand, rapid advances in experimental techniques allow for detailed experimental measurements of cell migration pathways, while, on the other, computational approaches allow for the modelling, analysis and understanding of such observations. The bulk-surface mechanobiochemical modelling approach presented in this work, set premises to study single cell migration through complex non-isotropic environments in two- and three-space dimensions.
{"title":"A bulk-surface mechanobiochemical modelling approach for single cell migration in two-space dimensions","authors":"David Hernandez-Aristizabal , Diego-Alexander Garzon-Alvarado , Carlos-Alberto Duque-Daza , Anotida Madzvamuse","doi":"10.1016/j.jtbi.2024.111966","DOIUrl":"10.1016/j.jtbi.2024.111966","url":null,"abstract":"<div><div>In this work, we present a mechanobiochemical model for two-dimensional cell migration which couples mechanical properties of the cell cytosol with biochemical processes taking place near or on the cell plasma membrane. The modelling approach is based on a recently developed mathematical formalism of evolving bulk-surface partial differential equations of reaction–diffusion type. We solve these equations using finite element methods within a moving-mesh framework derived from the weak formulation of the evolving bulk-surface PDEs. In the present work, the cell cytosol interior (bulk) dynamics are coupled to the cell membrane (surface) dynamics through non-homogeneous Dirichlet boundary conditions. The modelling approach exhibits both directed cell migration in response to chemical cues as well as spontaneous migration in the absence of such cues. As a by-product, the approach shows fundamental characteristics associated with single cell migration such as: (i) cytosolic and membrane polarisation, (ii) actin dependent protrusions, and (iii) continuous shape deformation of the cell during migration.</div><div>Cell migration is an ubiquitous process in life that is mainly triggered by the dynamics of the actin cytoskeleton and therefore is driven by both mechanical and biochemical processes. It is a multistep process essential for mammalian organisms and is closely linked to a vast diversity of processes; from embryonic development to cancer invasion. Experimental, theoretical and computational studies have been key to elucidate the mechanisms underlying cell migration. On one hand, rapid advances in experimental techniques allow for detailed experimental measurements of cell migration pathways, while, on the other, computational approaches allow for the modelling, analysis and understanding of such observations. The bulk-surface mechanobiochemical modelling approach presented in this work, set premises to study single cell migration through complex non-isotropic environments in two- and three-space dimensions.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111966"},"PeriodicalIF":1.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell-based mechanical models, such as the Cell Vertex Model (CVM), have proven useful for studying the mechanical control of epithelial tissue dynamics. We recently developed a statistical method called image-based parameter inference for formulating CVM model functions and estimating their parameters from image data of epithelial tissues. In this study, we employed Bayesian statistics to improve the utility and flexibility of image-based parameter inference. Tests on synthetic data confirmed that both our non-hierarchical and hierarchical Bayesian models provide accurate estimates of model parameters. By applying this method to Drosophila wings, we demonstrated that the reliability of parameter estimation is closely linked to the mechanical anisotropies present in the tissue. Moreover, we revealed that the cortical elasticity term is dispensable for explaining force-shape correlations in vivo. We anticipate that the flexibility of the Bayesian statistical framework will facilitate the integration of various types of information, thereby contributing to the quantitative dissection of the mechanical control of tissue dynamics.
{"title":"Bayesian parameter inference for epithelial mechanics","authors":"Xin Yan , Goshi Ogita , Shuji Ishihara , Kaoru Sugimura","doi":"10.1016/j.jtbi.2024.111960","DOIUrl":"10.1016/j.jtbi.2024.111960","url":null,"abstract":"<div><div>Cell-based mechanical models, such as the Cell Vertex Model (CVM), have proven useful for studying the mechanical control of epithelial tissue dynamics. We recently developed a statistical method called image-based parameter inference for formulating CVM model functions and estimating their parameters from image data of epithelial tissues. In this study, we employed Bayesian statistics to improve the utility and flexibility of image-based parameter inference. Tests on synthetic data confirmed that both our non-hierarchical and hierarchical Bayesian models provide accurate estimates of model parameters. By applying this method to <em>Drosophila</em> wings, we demonstrated that the reliability of parameter estimation is closely linked to the mechanical anisotropies present in the tissue. Moreover, we revealed that the cortical elasticity term is dispensable for explaining force-shape correlations <em>in vivo</em>. We anticipate that the flexibility of the Bayesian statistical framework will facilitate the integration of various types of information, thereby contributing to the quantitative dissection of the mechanical control of tissue dynamics.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"595 ","pages":"Article 111960"},"PeriodicalIF":1.9,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.jtbi.2024.111963
Mossa Merhi Reimert, Maya Katrin Gussmann, Anette Ella Boklund, Matt Denwood
Disease modelling at the livestock-wildlife interface is an important topic for which discrete-space models are used for the wildlife component. One prominent example is African Swine Fever, where wild boar play an influential role as reservoirs of disease spillover into domestic pig farms. In this paper, we present a simulation study that demonstrates the impact of seemingly arbitrary choices of landscape discretisation method on the inferred rate of spread within the model. We use an ordinary differential equation model to implement a simplified model of disease transmission between discrete groups of wild boar with spillover into domestic pig farms contained within a homogeneous landscape. We examine a range of scenarios whereby the landscape is discretised into wild boar patches of varying size and shape, and compare the rate of spread between domestic pig farms placed at fixed points on the landscape. Our results demonstrate a non-monotonic relationship between patch size and rate of spread, which is particularly unstable and unpredictable for square and triangular shaped patches. Discretisation of the landscape into hexagons appears to produce a more stable relationship between patch size and rate of spread for the three types of transmission kernel we investigated. Although the rate of disease spread does converge to a stable value, this occurs at patch sizes that are much smaller than would be used in practice for wild boar. We conclude that outputs of disease models containing a wildlife component should not be considered to be robust to arbitrary choices for patch size and placement, but rather as a source of uncertainty to be examined using sensitivity analysis. Furthermore, we strongly recommend the use of hexagons rather than squares or right triangles for landscape discretisation.
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