Dataset Information

Modular 3D In Vitro Artery-Mimicking Multichannel System for Recapitulating Vascular Stenosis and Inflammation.

ABSTRACT: Inflammation and the immune response in atherosclerosis are complex processes involving local hemodynamics, the interaction of dysfunctional cells, and various pathological environments. Here, a modular multichannel system that mimics the human artery to demonstrate stenosis and inflammation and to study physical and chemical effects on biomimetic artery models is presented. Smooth muscle cells and endothelial cells were cocultured in the wrinkled surface in vivo-like circular channels to recapitulate the artery. An artery-mimicking multichannel module comprised four channels for the fabrication of coculture models and assigned various conditions for analysis to each model simultaneously. The manipulation became reproducible and stable through modularization, and each module could be replaced according to analytical purposes. A chamber module for culture was replaced with a microfluidic concentration gradient generator (CGG) module to achieve the cellular state of inflamed lesions by providing tumor necrosis factor (TNF)-α, in addition to the stenosis structure by tuning the channel geometry. Different TNF-α doses were administered in each channel by the CGG module to create functional inflammation models under various conditions. Through the tunable channel geometry and the microfluidic interfacing, this system has the potential to be used for further comprehensive research on vascular diseases such as atherosclerosis and thrombosis.

SUBMITTER: Cho M

PROVIDER: S-EPMC8709401 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Risk stratification of asymptomatic carotid artery stenosis (ACAS) is still an issue for carotid revascularization. We sought to identify factors associated with symptomatic carotid artery stenosis (SCAS) using multimodal imaging techniques. Methods: We retrospectively collected data on patients who underwent carotid artery revascularization. Results from duplex sonography, computerized tomography angiography, brain magnetic resonance imaging (MRI), magnetic resonance angiography (MRA), perfusion-weighted imaging, and demographic profiles were compared between ACAS and SCAS patients. Differences in baseline characteristics between the two groups were balanced by the propensity matching score method. Multivariable regression analysis was performed to identify factors associated with symptomaticity of carotid artery stenosis. We compared the strength of associations between significant imaging factors and symptomatic carotid stenosis using C statistics. Results: A total of 259 patients (asymptomatic 57.1%, symptomatic 42.9%) with carotid stenosis were included. After 1:1 propensity score matching, the multivariable regression analysis revealed that the absence of plaque calcification [Odds ratio 0.41, 95% confidence interval (CI) 0.182-0.870, p = 0.023], deep white matter hyperintensity (DWMH; Odds ratio 3.46, 95% CI 1.842-6.682, p < 0.001), susceptibility vessel sign seen on gradient-echo MRI (Odds ratio 2.35, 95% CI 1.113-5.107, p = 0.027), and increased cerebral blood volume (CBV) seen on perfusion-weighted MRI (CBV; Odds ratio 2.17, 95% CI 1.075-4.454, p = 0.032) were associated with SCAS. The combination of these variables had a fair accuracy to classify SCAS (Area under the curve 0.733, 95% CI 0.662-0.803). Conclusions: We identified several multimodal imaging markers independently associated with SCAS. These markers may provide information to identify ACAS patients with high risk of ischemic stroke. Future studies are needed to predict SCAS using our findings in other independent cohorts.

Dataset Information

Modular 3D In Vitro Artery-Mimicking Multichannel System for Recapitulating Vascular Stenosis and Inflammation.

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