Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi-species bacterial communities, called “infection microbiomes,” that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi-scale modeling framework, known as template-and-anchor modeling, that allows the gradual integration of refined sub-models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases.

中文翻译：

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囊性纤维化作为一种​​全身性疾病的数学模型

囊性纤维化（CF）被广泛认为是一种肺部疾病，尽管它实际上是一种全身性疾病，其症状通常首先表现为胃肠功能障碍。囊性纤维化最终不仅会损害胰腺和肠道，还会损害肺、性腺、肝脏、肾脏、骨骼和心血管系统。它是由上皮离子通道蛋白 CFTR 基因的几种突变之一引起的。过去 80 年来，深入的研究和改进的抗菌治疗已将 CF 患者 (pwCF) 的预期寿命从几周稳步延长至 50 多年。此外，近年来出现了几种改善该疾病后遗症的药物，并且针对该疾病根本原因的显着治疗最近使一些但不是全部 pwCF 的健康状况得到了显着改善。然而，许多基本问题仍未得到解答。例如在肺部，氯化物分泌不足通常会扰乱上皮细胞的电化学平衡，并且在气道中导致厚厚的粘液和粘液斑块积聚，这些粘液和粘液斑块无法有效清除并提供一系列细菌和真菌群落的丰富滋生地。随后的感染通常会变成慢性，并且对抗生素治疗反应不佳，结果有时仅与目标病原体的药物敏感性微弱相关。此外，与单一目标病原体快速解决的急性感染相比，慢性感染通常涉及多物种细菌群落，称为“感染微生物组”，它们发展自己的生态和进化动态。目前不可能设计出完整的 CF 数学模型，但为该疾病的许多不同驱动因素设计模型是可行的。基于这些不断增长但孤立的建模工作，我们在下面讨论了多尺度建模框架（称为模板和锚定建模）的可行性，该框架允许逐步集成具有不同粒度的细化子模型。本文首先回顾了 CF 最重要的生物医学方面，随后描述了已经存在或有可能加深我们对该疾病的多个方面及其相互关系的理解的数学建模方法。这里提出的方法背后的概念思想不仅涉及 CF，而且可以转化为其他系统性疾病。