[Hemodynamics simulation and analysis of left coronary artery aneurysms with concomitant stenosis].

The hemodynamic parameters in arteries are difficult to measure non-invasively, and the analysis and prediction of hemodynamic parameters based on computational fluid dynamics (CFD) has become one of the important research hotspots in biomechanics. This article establishes 15 idealized left coronary artery bifurcation models with concomitant stenosis and aneurysm lesions, and uses CFD method to numerically simulate them, exploring the effects of left anterior descending branch (LAD) stenosis rate and curvature radius on the hemodynamics inside the aneurysm. This study compared models with different stenosis rates and curvature radii and found that as the stenosis rate increased, the oscillatory shear index (OSI) and relative residence time (RRT) showed a trend of increase; In addition, the decrease in curvature radius led to an increase in the degree of vascular curvature and an increased risk of vascular aneurysm rupture.

Molecular basis of transport of surface functionalised gold nanoparticles to pulmonary surfactant.

Ligands like alkanethiol ( dodecanethiol, hexadecanethiol, ) and polymers ( poly(vinyl pyrrolidone), polyethylene glycol-thiol) capped to the gold nanoparticles (AuNPs) are widely used in biomedical field as drug carriers and as promising materials for probing and manipulating cellular processes. Ligand functionalised AuNPs are known to interact with the pulmonary surfactant (PS) monolayer once reaching the alveolar region. Therefore, it is crucial to understand the interaction between AuNPs and PS monolayers.

Inverse identification of hyperelastic constitutive parameters of skeletal muscles via optimization of AI techniques.

Studies on the deformation characteristics and stress distribution in loaded skeletal muscles are of increasing importance. Reliable prediction of hyperelastic material parameters requires an inverse process, which possesses challenges. This work proposes two inverse procedures to identify the hyperelastic material parameters of skeletal muscles.

Effect of concentration of PEG coated gold nanoparticle on lung surfactant studied with coarse-grained molecular dynamics simulations.

The surface modification of nanoparticles can not only change the physical and chemical properties of particles, such as the hydrophilic and hydrophobic properties and surface charges of nanoparticles to a certain extent, but also bring new functions to nanoparticles, such as membrane permeability and targeting. Inhaled nanoparticles (NPs) are experienced by the first biological barrier inside the alveolus known as lung surfactant (LS), consisting of phospholipids and proteins in the form of the monolayer at the air-water interface. Inhaled NPs can reach deep into the lungs and interfere with the biophysical properties of the lung components.

Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.

In order to have research on the deformation characteristics and mechanical properties of human red blood cells (RBCs), finite element models of RBC optical tweezers stretching and atomic force microscope (AFM) indentation were established. Non-linear elasticity of cell membrane was determined by using the neo-Hookean hyperelastic material model, and the deformation of RBC during stretching and indentation had been researched in ABAQUS, respectively. Considering the application of machine learning (ML) in material parameters identification, ML algorithm was combined with finite element (FE) method to identify the constitutive parameters.