A mathematical model for intracellular NO and ROS dynamics in vascular endothelial cells activated by exercise-induced wall shear stress.
Math Biosci
; 359: 109009, 2023 05.
Article
en En
| MEDLINE
| ID: mdl-37086782
ABSTRACT
Vascular endothelial cells (ECs) residing in the innermost layer of blood vessels are exposed to dynamic wall shear stress (WSS) induced by blood flow. The intracellular nitric oxide (NO) and reactive oxygen species (ROS) in ECs modulated by the dynamic WSS play important roles in endothelial functions. Mathematical modeling is a popular methodology for biophysical studies. It can not only explain existing cell experiments, but also reveal the underlying mechanism. However, the previous mathematical models of NO dynamics in ECs are limited to the static WSS induced by constant flow, while arterial blood flow is a periodic pulsatile flow with varying amplitude and frequency at different exercise intensities. In this study, a mathematical model of intracellular NO and ROS dynamics activated by dynamic WSS based on the in vitro cell experiments is developed. With the hypothesis of the viscoelastic body, the Kelvin model is adopted to simulate the mechanosensors on EC. Thus, the NO dynamics activated by dynamic shear stresses induced by constant flow, pulsatile flow, and oscillatory flow are analyzed and compared. Moreover, the roles of ROS have been considered for the first time in the modeling of NO dynamics in ECs based on the analysis of cell experiments. The predictions of the proposed model coincide fairly well with the experimental data when ECs are subjected to exercise-induced WSS. The mechanism is elucidated that WSS induced by moderate-intensity exercise is most favorable to NO production in ECs. This study can provide valuable insights for further study of NO and ROS dynamics in ECs and help develop appropriate exercise regimens for improving endothelial functions.
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Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Células Endoteliales
/
Óxido Nítrico
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Math Biosci
Año:
2023
Tipo del documento:
Article