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Recent Advances in Computational Modeling of Biomechanics and Biorheology of Red Blood Cells in Diabetes.
Deng, Yi-Xiang; Chang, Hung-Yu; Li, He.
Afiliación
  • Deng YX; School of Engineering, Brown University, Providence, RI 02912, USA.
  • Chang HY; Division of Applied Mathematics, Brown University, Providence, RI 02912, USA.
  • Li H; Center for Biomedical Engineering, Brown University, Providence, RI 02912, USA.
Biomimetics (Basel) ; 7(1)2022 Jan 13.
Article en En | MEDLINE | ID: mdl-35076493
ABSTRACT
Diabetes mellitus, a metabolic disease characterized by chronically elevated blood glucose levels, affects about 29 million Americans and more than 422 million adults all over the world. Particularly, type 2 diabetes mellitus (T2DM) accounts for 90-95% of the cases of vascular disease and its prevalence is increasing due to the rising obesity rates in modern societies. Although multiple factors associated with diabetes, such as reduced red blood cell (RBC) deformability, enhanced RBC aggregation and adhesion to the endothelium, as well as elevated blood viscosity are thought to contribute to the hemodynamic impairment and vascular occlusion, clinical or experimental studies cannot directly quantify the contributions of these factors to the abnormal hematology in T2DM. Recently, computational modeling has been employed to dissect the impacts of the aberrant biomechanics of diabetic RBCs and their adverse effects on microcirculation. In this review, we summarize the recent advances in the developments and applications of computational models in investigating the abnormal properties of diabetic blood from the cellular level to the vascular level. We expect that this review will motivate and steer the development of new models in this area and shift the attention of the community from conventional laboratory studies to combined experimental and computational investigations, aiming to provide new inspirations for the development of advanced tools to improve our understanding of the pathogenesis and pathology of T2DM.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Biomimetics (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Biomimetics (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos