A computational study of leukocyte adhesion and its effect on flow pattern in microvessels

Area of Science:

• * Biophysics
• * Computational Biology
• * Fluid Dynamics

Background:

• * Leukocyte adhesion and rolling are critical in inflammatory responses.
• * Previous models often simplified cell mechanics, neglecting deformability and rolling.
• * Understanding these dynamics is key for targeted therapies.

Purpose of the Study:

• * To computationally model and simulate the adhesive rolling of deformable leukocytes.
• * To investigate the influence of cell deformability and concentration on rolling characteristics and flow resistance.
• * To assess the impact of neglecting cell deformability and rolling in previous models.

Main Methods:

• * Three-dimensional computational modeling using the immersed boundary method for cell deformation.
• * Monte Carlo simulation for receptor/ligand interactions.
• * Simulation of leukocyte rolling in parabolic shear flow within microchannels.

Main Results:

• * Compliant leukocytes roll slower and more stably than rigid ones.
• * Hydrodynamic interactions decrease rolling velocity, inversely proportional to separation distance.
• * Increased cell concentration reduces velocity fluctuations and enhances rolling stability, with a more pronounced effect on rigid cells.
• * Neglecting cell deformability and rolling can significantly overpredict flow resistance and drag force.
• * Higher cell concentration increases flow resistance and reduces fluid drag, leading to slower, more stable rolling.

Conclusions:

• * Cell deformability and concentration are crucial factors in leukocyte rolling dynamics.
• * Computational models must incorporate cell mechanics for accurate predictions of flow resistance and drag.
• * Findings provide insights into leukocyte behavior in microfluidic environments and inflammatory processes.