Effects of the Haemodynamic Stimulus on the Location of Carotid Plaques Based on a Patient-Specific Mechanobiological Plaque Atheroma Formation Model

Impact of geometric and hemodynamic changes on a mechanobiological model of atherosclerosis

BACKGROUND AND OBJECTIVE

In this work, the analysis of the importance of hemodynamic updates on a mechanobiological model of atheroma plaque formation is proposed.

METHODS

For that, we use an idealized and axisymmetric model of carotid artery. In addition, the behavior of endothelial cells depending on hemodynamical changes is analyzed too. A total of three computational simulations are carried out and their results are compared: an uncoupled model and two models that consider the opposite behavior of endothelial cells caused by hemodynamic changes. The model considers transient blood flow using the Navier-Stokes equation. Plasma flow across the endothelium is determined with Darcy's law and the Kedem-Katchalsky equations, considering the three-pore model, which is also employed for the flow of substances across the endothelium. The behavior of the considered substances in the arterial wall is modeled with convection-diffusion-reaction equations, and the arterial wall is modeled as a hyperelastic Yeoh's material.

RESULTS

Significant variations are noted in both the morphology and stenosis ratio of the plaques when comparing the uncoupled model to the two models incorporating updates for geometry and hemodynamic stimuli. Besides, the phenomenon of double-stenosis is naturally reproduced in the models that consider both geometric and hemodynamical changes due to plaque growth, whereas it cannot be predicted in the uncoupled model.

CONCLUSIONS

The findings indicate that integrating the plaque growth model with geometric and hemodynamic settings is essential in determining the ultimate shape and dimensions of the carotid plaque.

Integrating Computational and Biological Hemodynamic Approaches to Improve Modeling of Atherosclerotic Arteries

Atherosclerosis is the primary cause of cardiovascular disease, resulting in mortality, elevated healthcare costs, diminished productivity, and reduced quality of life for individuals and their communities. This is exacerbated by the limited understanding of its underlying causes and limitations in current therapeutic interventions, highlighting the need for sophisticated models of atherosclerosis. This review critically evaluates the computational and biological models of atherosclerosis, focusing on the study of hemodynamics in atherosclerotic coronary arteries. Computational models account for the geometrical complexities and hemodynamics of the blood vessels and stenoses, but they fail to capture the complex biological processes involved in atherosclerosis. Different in vitro and in vivo biological models can capture aspects of the biological complexity of healthy and stenosed vessels, but rarely mimic the human anatomy and physiological hemodynamics, and require significantly more time, cost, and resources. Therefore, emerging strategies are examined that integrate computational and biological models, and the potential of advances in imaging, biofabrication, and machine learning is explored in developing more effective models of atherosclerosis.

SEL1L3 as a link molecular between renal cell carcinoma and atherosclerosis based on bioinformatics analysis and experimental verification

BACKGROUND

Renal cancer, the most common type of kidney cancer, develops in the renal tubular epithelium. Atherosclerosis of the aorta is the primary cause of atherosclerosis. However, the underlying mechanisms remain unclear.

METHODS

The renal clear cell carcinoma RNA sequence profile was obtained from The Cancer Genome Atlas (TCGA) database, and the atherosclerosis datasets GSE28829 and GSE43292 based on GPL570 and GPL6244 was obtained from the Gene Expression Omnibus (GEO) database. The difference and hub genes were identified by the Limma protein-protein interaction (PPI) network in R software. Functional enrichment, survival, and immunoinfiltration analyses were performed. The role of SEL1L3 in the ErbB/PI3K/mTOR signaling pathway, apoptosis, invasion, cell cycle, and inflammation was analyzed using western blotting.

RESULTS

764 DEGs were identified from TCGA Kidney Renal Clear Cell Carcinoma (KIRC) dataset. A total of 344 and 117 DEGs were screened from the GSE14762 and GSE53757 datasets, respectively. Functional enrichment analysis results primarily indicated enrichment in the transporter complex, DNA-binding transcription activator activity, morphogenesis of the embryonic epithelium, stem cell proliferation, adrenal overactivity and so on. Fifteen common DEGs overlapped among the three datasets. The PPI network revealed that SEL1L3 was the core gene. Survival analysis showed that lower SEL1L3 expression levels led to a worse prognosis. Immune cell infiltration analysis showed that SEL1L3 expression was significantly correlated with antibody-drug conjugates (aDC), B cells, eosinophils, interstitial dendritic cells (iDC), macrophages, and more.

CONCLUSIONS

SEL1L3 plays an important role in renal clear cell carcinoma and atherosclerosis and may be a potential link between them.

Plexin D1 mediates disturbed flow-induced M1 macrophage polarization in atherosclerosis

Atherosclerosis preferentially develops at bifurcations exposed to disturbed flow. Plexin D1 (PLXND1) responds to mechanical forces and drives macrophage accumulation in atherosclerosis. Here, multiple strategies were used to identify the role of PLXND1 in site-specific atherosclerosis. Using computational fluid dynamics and three-dimensional light-sheet fluorescence-microscopy, the elevated PLXND1 in M1 macrophages was mainly distributed in disturbed flow area of ApoE^-/- carotid bifurcation lesions, and visualization of atherosclerosis in vivo was achieved by targeting PLXND1. Subsequently, to simulate the microenvironment of bifurcation lesions in vitro, we co-cultured oxidized low-density lipoprotein (oxLDL)-treated THP-1-derived macrophages with shear-treated human umbilical vein endothelial cells (HUVECs). We found that oscillatory shear induced the increase of PLXND1 in M1 macrophages, and knocking down PLXND1 inhibited M1 polarization. Semaphorin 3E, the ligand of PLXND1 which was highly expressed in plaques, strongly enhanced M1 macrophage polarization via PLXND1 in vitro. Our findings provide insights into pathogenesis in site-specific atherosclerosis that PLXND1 mediates disturbed flow-induced M1 macrophage polarization.

The effects of high-intensity interval training and moderate-intensity continuous training on visceral fat and carotid hemodynamics parameters in obese adults

Objectives

The present study aimed to examine the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on visceral fat and hemodynamic parameters in obese adults.

Methods

Fifty-two males were included in this study and divided into three groups: HIIT group (n = 21, age = 20.86 ± 1.62 years, BF (%) = 30.10 ± 5.02), MICT group (n = 22, age = 20.76 ± 1.14 years, BF (%) = 30.19 ± 5.76), and control group (CON) (n = 9, age = 21.38 ± 1.77 years, BF (%) = 30.40 ± 5.10). The HIIT and MICT groups received the exercise intervention three to four times per week for eight weeks (HIIT: exercise intensity 80–95% HRmax, circuit; MICT: exercise intensity 60–70% HRmax, running), and the control (CON) group received health education and guidance without exercise intervention. The body compositions and serum lipid indexes were tested to calculated LAP and VAI. The color doppler ultrasound diagnostic technology was used to test the artery diameter and blood velocity before and after the intervention. Based on the test data, MATLAB software and Womersley theory were used to calculate the hemodynamic parameters of the common carotid artery, including wall shear stress, flow rate, blood pressure, oscillatory shear index, elasticity modulus, dynamic resistance, artery diameter, arterial stiffness, circumferential strain and pulsatility index.

Results

We found that lipid accumulation product (LAP) was significantly decreased in both the HIIT group (p < 0.01) and MICT (p < 0.05) group but not in the CON group (p > 0.05). In contrast, visceral adiposity index (VAI) decreased in both the HIIT and MICT groups and increased in the CON group, although the difference among groups was not significant (p > 0.05). After 8 weeks of intervention, the blood velocity and wall shear stress were greater after HIIT and MICT intervention (p < 0.01). Artery diameter, oscillatory shear index, arterial stiffness, and pulsatility index decreased significantly, and circumferential strain increased significantly in the HIIT group (all, p < 0.01, p < 0.05) but not in the MICT group (p > 0.05). Dynamic resistance was significantly decreased in the MICT group. There was no difference in the CON group after the period of intervention (all, p > 0.05). LAP was positively related to artery diameter (r = 0.48, p = 0.011), blood pressure (r = 0.46, p = 0.002), flow rate (r = 0.31, p = 0.04), oscillatory shear index (r = 0.44, p = 0.03), and elasticity modulus (r = 0.33, p = 0.029) but inversely related to circumferential strain (r = −0.36, p = 0.028). The VAI was also positively associated with artery diameter (r = 0.33, p = 0.03), elasticity modulus (r = 0.38, p = 0.009), and arterial stiffness (r = 0.39, p = 0.012). In addition, the VAI was negatively correlated with the circumferential strain (r = −0.33, p = 0.04).

Conclusion

The present study demonstrated that both HIIT and MICT exercises for 8 weeks could effectively enhance visceral fat indices and partial hemodynamic parameters. Therefore, HIIT and MICT exert important effects on reducing fat content and improving hemodynamic environment. But HIIT on oscillatory shear index, arterial stiffness, circumferential strain, and pulsatility index was superior to MICT. In addition, there are close correlations between visceral fat and partial hemodynamic parameters of the common carotid artery.