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Simulation scripts for studying the effect of circulating cell clusters on hemorheology

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Circulating cell clusters aggravate the hemorheological abnormalities in COVID-19

This repo contains input files for the simulation of three types of clusters in blood flow under a shear rate of 10 1/s: WBC-WBC (white-blood-cell with white-blood-cell), PLT-PLT (platelet with platelet), and WBC-PLT (white-blood-cell with platelet)

These codes were used in to investigate the dynamics of different types of circulating cell clusters and study how COVID-19 affects the rheology of blood.

This work is published in:

Circulating cell clusters aggravate the hemorheological abnormalities in COVID-19
Elahe Javadi, He Li, Ander Dorken Gallastegi, Galit H. Frydman, Safa Jamali, George Em Karniadakis
Biophysical Journal · 2022

Software/package requirements

All simulation data reported in the paper are generated through LAMMPS code

Abstract and Significance

Microthrombi and circulating cell clusters are common microscopic findings in patients with coronavirus disease 2019 (COVID-19) at different stages in the disease course, implying that they may function as the primary drivers in disease progression. Inspired by a recent flow imaging cytometry study of the blood samples from patients with COVID-19, we perform computational simulations to investigate the dynamics of different types of circulating cell clusters, namely white blood cell (WBC) clusters, platelet clusters, and red blood cell clusters, over a range of shear flows and quantify their impact on the viscosity of the blood. Our simulation results indicate that the increased level of fibrinogen in patients with COVID-19 can promote the formation of red blood cell clusters at relatively low shear rates, thereby elevating the blood viscosity, a mechanism that also leads to an increase in viscosity in other blood diseases, such as sickle cell disease and type 2 diabetes mellitus. We further discover that the presence of WBC clusters could also aggravate the abnormalities of local blood rheology. In particular, the extent of elevation of the local blood viscosity is enlarged as the size of the WBC clusters grows. On the other hand, the impact of platelet clusters on the local rheology is found to be negligible, which is likely due to the smaller size of the platelets. The difference in the impact of WBC and platelet clusters on local hemorheology provides a compelling explanation for the clinical finding that the number of WBC clusters is significantly correlated with thrombotic events in COVID-19 whereas platelet clusters are not. Overall, our study demonstrates that our computational models based on dissipative particle dynamics can serve as a powerful tool to conduct quantitative investigation of the mechanism causing the pathological alterations of hemorheology and explore their connections to the clinical manifestations in COVID-19.

Significance

Inspired by a recent flow imaging cytometry study of the blood samples from patients with coronavirus disease 2019, we perform a computational investigation of the dynamics of different types of circulating cell clusters, namely white blood cell (WBC) clusters, platelet clusters, and red blood cell clusters over a range of shear flows and quantify their impact on the viscosity of the blood. Our simulation results suggest that formation of WBC and red blood cell clusters could cause a significant increase in the local viscosity of the blood, whereas the impact of platelet clusters on the rheology is negligible. This finding provides a possible explanation for the clinical finding that the number of WBC clusters is significantly correlated with thrombotic events.

Contributors

This work was done by Elahe Javadi, He Li, Ander Dorken Gallastegi, Galit H. Frydman, Safa Jamali, and George Em Karniadakis.

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