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推导 [Formula: see text]C 呼气测试曲线所基于的代谢率的机制推断。

Mechanistic inference of the metabolic rates underlying [Formula: see text]C breath test curves.

机构信息

Department of Epidemiology, University of Michigan, 1415 Washington Heights, Ann Arbor, 48109, MI, United States.

Scottish Universities Environmental Research Centre, University of Glasgow, Rankine Avenue, East Kilbride, G75 0QF, United Kingdom.

出版信息

J Pharmacokinet Pharmacodyn. 2023 Jun;50(3):203-214. doi: 10.1007/s10928-023-09847-x. Epub 2023 Feb 15.

Abstract

Carbon stable isotope breath tests offer new opportunities to better understand gastrointestinal function in health and disease. However, it is often not clear how to isolate information about a gastrointestinal or metabolic process of interest from a breath test curve, and it is generally unknown how well summary statistics from empirical curve fitting correlate with underlying biological rates. We developed a framework that can be used to make mechanistic inference about the metabolic rates underlying a C breath test curve, and we applied it to a pilot study of C-sucrose breath test in 20 healthy adults. Starting from a standard conceptual model of sucrose metabolism, we determined the structural and practical identifiability of the model, using algebra and profile likelihoods, respectively, and we used these results to develop a reduced, identifiable model as a function of a gamma-distributed process; a slower, rate-limiting process; and a scaling term related to the fraction of the substrate that is exhaled as opposed to sequestered or excreted through urine. We demonstrated how the identifiable model parameters impacted curve dynamics and how these parameters correlated with commonly used breath test summary measures. Our work develops a better understanding of how the underlying biological processes impact different aspect of C breath test curves, enhancing the clinical and research potential of these C breath tests.

摘要

碳稳定同位素呼吸测试为更好地了解健康和疾病中的胃肠道功能提供了新的机会。然而,通常不清楚如何从呼吸测试曲线中分离出有关感兴趣的胃肠道或代谢过程的信息,并且通常也不知道经验曲线拟合的汇总统计数据与基础生物学速率的相关性如何。我们开发了一个框架,可以用于对 C 呼吸测试曲线下的代谢速率进行机制推断,我们将其应用于 20 名健康成年人的 C-蔗糖呼吸测试的初步研究中。从蔗糖代谢的标准概念模型开始,我们分别使用代数学和轮廓似然度来确定模型的结构和实际可识别性,并使用这些结果来开发一个简化的、可识别的模型,作为伽马分布过程、较慢的、限速过程以及与作为呼出物而不是被隔离或通过尿液排泄的底物分数相关的缩放项的函数。我们展示了可识别模型参数如何影响曲线动态,以及这些参数如何与常用的呼吸测试汇总指标相关。我们的工作更好地了解了基础生物学过程如何影响 C 呼吸测试曲线的不同方面,从而增强了这些 C 呼吸测试的临床和研究潜力。

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