Inferring epithelial tissue mechanics through data-efficient multi-fidelity modelling

通过数据高效的多保真度建模推断上皮组织力学

• 批准号: BB/Y514020/1
• 负责人: Alexander Fletcher
• 金额: $ 24.92万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FY514020%2F1
• 关键词: Inferring; epithelial; tissue; mechanics; through

How do the organs in our body control their shape and structure? We know that when they fail to do this, we get overgrowth, and frequently cancer. If we can understand these control systems, perhaps we will be able to understand what happens when tissues lose their correct structure, and go on to develop more effective treatments. Proper control of tissue structure comes about due to a balance of mechanical forces acting within, and between, the cells that make up a tissue. Therefore, quantifying the mechanics of cells and tissues is essential to understanding their shape and structure.Recently, our team members generated a large set of images and videos showing how, in the lab, a special type of tissue forms a single sheet of cells strongly adhering to their neighbours. We also created a computer model that allowed us to explore how different balances of mechanical forces can lead to this sheet of cells having different shapes and structures. However, it is difficult to precisely pin down the strength of each mechanical force in the model from the images, because it takes a while for the model to run.In this project, we will use new and existing artificial intelligence and machine learning methods to learn these mechanical properties much faster from our data, by bringing together information gleaned from simpler versions of our model in an automated way. As a result, we will come up with better estimates for these mechanical properties, and a better understanding of how cell sheets attain their characteristic shapes and structures. We will write software to do this that can also be used by other scientists studying similar problems in areas of biology ranging from cell and developmental biology to synthetic biology, regenerative medicine, and cancer research.

我们体内的器官是如何控制它们的形状和结构的？我们知道，当他们不能做到这一点，我们得到过度生长，并经常癌症。如果我们能够理解这些控制系统，也许我们将能够理解当组织失去正确的结构时会发生什么，并继续开发更有效的治疗方法。对组织结构的适当控制是由于构成组织的细胞内和细胞之间的机械力的平衡而产生的。因此，量化细胞和组织的力学对于理解它们的形状和结构至关重要。最近，我们的团队成员制作了一系列图像和视频，展示了在实验室中，一种特殊类型的组织如何形成一片细胞，这些细胞强烈地粘附在它们的邻居身上。我们还创建了一个计算机模型，使我们能够探索机械力的不同平衡如何导致这片细胞具有不同的形状和结构。然而，很难从图像中精确地确定模型中每个机械力的强度，因为模型运行需要一段时间。在这个项目中，我们将使用新的和现有的人工智能和机器学习方法，通过自动化的方式将从我们模型的简单版本中收集的信息结合起来，从我们的数据中更快地学习这些机械特性。因此，我们将对这些力学性质做出更好的估计，并更好地理解细胞片如何获得其特征形状和结构。我们将编写软件来实现这一点，这些软件也可以被其他科学家用于研究生物学领域的类似问题，从细胞和发育生物学到合成生物学，再生医学和癌症研究。