Establishment of spatio-temporal multiscale multispecies liver tissue models by analysis of experimental images for systems medicine

拟议的项目被设想为从组织、细胞和蛋白质的结构和功能方面探索人体综合生理功能的一部分。建议项目有两个主要目标：(1)直接从实验图像模态建立基于个体细胞的生物组织时空多尺度模型的自动化和标准化(2)应用这些组织模型阐明不同物种肝部分切除后肝脏再生的机制，更好地了解人类肝衰竭。人工构建预测组织模型，将实验数据直接参数化真实结构和动力学仍然非常具有挑战性。因此，组织模型构建的自动化有可能在科学界开辟一个全新的潜在模型用户群体。只有成功地建立模型构建的鲁棒自动化，未来才有可能在科学中，特别是在患者治疗中大规模使用这种复杂的组织模型。在这条道路上，模型的标准化，例如建立全面的模型描述语言，将发挥重要作用。只有明确的模型描述才能确保模型的可重复性，这是通过建立在以前的工作上进行持续改进的重要基础。本项目将建立的时空肝脏模型就是这种方法的例证。此外，一般概念和技术将广泛应用于系统生物学和系统医学。此外，我们将利用开发的PHx后肝脏再生模型来解决临床相关问题，即为什么部分肝脏切除后肝脏再生的迷人能力在一些患者中失败导致高死亡率。了解导致肝功能衰竭的过程对于改善肝移植和肝癌治疗至关重要，例如通过模型模拟更好地评估个体患者肝切除手术的风险。开发的模型将整合遗传、分子、组织和器官尺度，因此将允许在健康和受损的脂肪肝中真正多尺度地表示肝脏组织结构和动力学。此外，我们将研究和模拟一种使用间充质干细胞的新治疗方法，初步结果表明，这有可能在患者护理方面迈出重要一步。

The proposed project is envisioned as being part of the search for understanding of the integrated physiological function of the human body in terms of structure and function of tissues, cells and proteins. There are two main objectives of the proposed project: (1) Automatization and standardization of creation of individual-cell-based spatio-temporal multi-scale models for biological tissues directly from experimental image modalities(2) Application of these tissue models to elucidate the mechanisms behind liver regeneration after partial liver resection in different species to better understand liver failure in humanManual construction of predictive tissue models where realistic structures and dynamics are parameterized directly by experimental data is still very challenging. Therefore, automatization of tissue model construction has the potential to open up a whole new group of possible model users in the scientific community. Future large-scale use of such complex tissue models in science and especially in patient therapy will only be possible if robust automatization of model construction can successfully be established.Along this path, standardization of models, for example by establishment of comprehensive model description languages, will play an important role. Only unambiguous model description will ensure model reproducibly that is an important foundation for their continuous improvement by building on previous work. The spatio-temporal liver models that will be established in this project exemplify this approach. Moreover, the general concepts and techniques will be widely applicable in systems biology and systems medicine. Furthermore, we will utilize the developed model for liver regeneration after PHx to address the clinically relevant question of why the fascinating ability of liver to regenerate after partial liver resection in some patients fails leading to high mortality rates. Understanding the processes leading to this liver failure is of utmost importance to improve for example liver transplantation and treatment of liver cancer for example by better assessing the risk of liver resection surgery for individual patients based on model simulations. The developed models will integrate genetic, molecular, tissue and organ scales and therefore will allow for a truly multiscale representation of liver tissue structures and dynamics in healthy and damaged fatty liver. Moreover, we will study and model a novel treatment using mesenchymal stem cells that, as preliminary results suggest, has the potential to be a significant step forward in patient care.