Red blood cells aggregates transport for finite concentration

TL;DR

This study uses 2D numerical simulations to analyze how different levels of RBC adhesion affect blood flow and oxygen transport, revealing that moderate adhesion enhances transport while excessive adhesion impairs it.

Contribution

It provides the first systematic analysis of the non-monotonic effects of RBC adhesion energy on blood flow and oxygen delivery in a simplified model.

Findings

Moderate adhesion improves RBC flux and oxygen transport.

Excessive adhesion reduces blood flow and oxygen delivery.

Non-monotonic relationship between adhesion energy and flow efficiency.

Abstract

Red blood cells (RBCs) are responsible for transporting oxygen and various metabolites to tissues and organs, as well as removing waste. Several cardiovascular diseases can impair these functions. For instance, in diabetes, increased RBC aggregation can lead to blood occlusion, thereby depriving tissues of efficient oxygen delivery. Interestingly, RBC adhesion occurs not only in disease states but also under physiological conditions, with the key difference being that adhesion is reversible in healthy situations. This paper focuses on numerical simulations in 2D, exploring different adhesion energies (both physiological and pathological) alongside varying flow strengths and hematocrit levels. A systematic analysis of RBC flux and viscosity is conducted. A remarkable finding is that moderate adhesion energy (within the physiological range) enhances RBC transport, thereby improving oxygen delivery to tissues. This provides insight into why RBC adhesion is present under normal conditions. Conversely, increasing adhesion energy beyond a certain point causes a collapse in RBC flux, thus reducing oxygen transport. We provide a basic explanation for the non-monotonic effect of adhesion energy on blood flow efficiency. This finding serves as an initial step in understanding the impact (both positive and negative) of RBC adhesion before addressing this issue in complex networks inspired by realistic microvasculatures.