What is it about?

Too high or too low potassium levels can have dangerous consequences. Potassium balance is achieved by tight regulation of potassium intake with excretion as well as a balance between extra- and intracellular potassium. There are a multitude of physiological processes involved in the regulation of potassium balance. However, how these processes come together is not well understood. This makes this problems well-suited for mathematical modeling. In this study, we developed a mathematical model of potassium homeostasis that includes the feedforward and feedback signals involved in potassium homeostasis. Using this model we were able to quantify the impact of individual regulatory mechanisms as well as test the impact of a hypothesized signal.

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Why is it important?

Dysregulation of potassium is a common, potentially dangerous side effect of many pathologies and medications. Potassium imbalance can lead to muscle weakness, fatigue, cardiac arrythmias, and in severe, untreated cases, may cause death. The study of potassium homeostasis is an active area of research, though few mathematical models have studies the impact of its regulatory mechanisms. Additionally, some signals have not be fully discovered. In this study, we developed a mathematical model that includes known regulatory mechanisms as well as provided computational support for a hypothesized additional signal. This computational model can be extended to include pathologies and medications as well as fitted to provide personalized predictions for individual patients to predict risk of low or high potassium levels.

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This page is a summary of: A mathematical model of potassium homeostasis: Effect of feedforward and feedback controls, PLoS Computational Biology, December 2022, PLOS,
DOI: 10.1371/journal.pcbi.1010607.
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