Schmid College of Science and Technology, Chapman University, 1 University Drive, Orange, CA 92866, USA.
Department of Mathematics, University of North Texas, Denton, TX 76203, USA.
J R Soc Interface. 2020 Sep;17(170):20200232. doi: 10.1098/rsif.2020.0232. Epub 2020 Sep 9.
Most biological functional systems are complex, and this complexity is a fundamental driver of diversity. Because input parameters interact in complex ways, a holistic understanding of functional systems is key to understanding how natural selection produces diversity. We present uncertainty quantification (UQ) as a quantitative analysis tool on computational models to study the interplay of complex systems and diversity. We investigate peristaltic pumping in a racetrack circulatory system using a computational model and analyse the impact of three input parameters (Womersley number, compression frequency, compression ratio) on flow and the energetic costs of circulation. We employed two models of peristalsis (one that allows elastic interactions between the heart tube and fluid and one that does not), to investigate the role of elastic interactions on model output. A computationally cheaper surrogate of the input parameter space was created with generalized polynomial chaos expansion to save computational resources. Sobol indices were then calculated based on the generalized polynomial chaos expansion and model output. We found that all flow metrics were highly sensitive to changes in compression ratio and insensitive to Womersley number and compression frequency, consistent across models of peristalsis. Elastic interactions changed the patterns of parameter sensitivity for energetic costs between the two models, revealing that elastic interactions are probably a key physical metric of peristalsis. The UQ analysis created two hypotheses regarding diversity: favouring high flow rates (where compression ratio is large and highly conserved) and minimizing energetic costs (which avoids combinations of high compression ratios, high frequencies and low Womersley numbers).
大多数生物功能系统都是复杂的，这种复杂性是多样性的根本驱动因素。由于输入参数以复杂的方式相互作用，因此全面了解功能系统是理解自然选择如何产生多样性的关键。我们提出不确定性量化 (UQ) 作为一种定量分析工具，用于研究复杂系统和多样性的相互作用。我们使用计算模型研究了赛道循环系统中的蠕动泵送，并分析了三个输入参数（沃默斯利数、压缩频率、压缩比）对流动和循环能量成本的影响。我们使用了两种蠕动模型（一种允许心脏管和流体之间的弹性相互作用，另一种则不允许），以研究弹性相互作用对模型输出的影响。使用广义多项式混沌扩展创建了输入参数空间的计算成本更低的替代物，以节省计算资源。然后根据广义多项式混沌扩展和模型输出计算了 Sobol 指数。我们发现，所有流量指标对压缩比的变化都非常敏感，而对沃默斯利数和压缩频率不敏感，这在蠕动模型中是一致的。弹性相互作用改变了两个模型之间能量成本的参数敏感性模式，表明弹性相互作用可能是蠕动的一个关键物理指标。UQ 分析提出了两个关于多样性的假设：有利于高流量率（压缩比大且高度保守）和最小化能量成本（避免高压缩比、高频率和低沃默斯利数的组合）。
