Vascular smooth muscle cells (VSMCs), the major cell type in the arterial vessel wall, have a contractile phenotype that maintains the normal vessel structure and function under physiological conditions. In response to stress or vascular injury, contractile VSMCs can switch to a less differentiated state (synthetic phenotype) to acquire the proliferative, migratory, and synthetic capabilities for tissue reparation. Imbalances in VSMCs phenotypic switching can result in a variety of cardiovascular diseases, including atherosclerosis, in-stent restenosis, aortic aneurysms, and vascular calcification. It is very important to identify the molecular mechanisms regulating VSMCs phenotypic switching to prevent and treat cardiovascular diseases with high morbidity and mortality. However, the key molecular mechanisms and signaling pathways participating in VSMCs phenotypic switching have still not been fully elucidated despite long-term efforts by cardiovascular researchers. In this review, we provide an updated summary of the recent studies and systematic knowledge of VSMCs phenotypic switching in atherosclerosis, in-stent restenosis, aortic aneurysms, and vascular calcification, which may help guide future research and provide novel insights into the prevention and treatment of related diseases.

Background A noninvasive coronary CT angiography (CCTA)-based radiomics technique may facilitate the identification of vulnerable plaques and patients at risk for future adverse events. Purpose To assess whether a CCTA-based radiomic signature (RS) of vulnerable plaques defined with intravascular US was associated with increased risk for future major adverse cardiac events (MACE). Materials and Methods In a retrospective study, an RS of vulnerable plaques was developed and validated using intravascular US as the reference standard. The RS development data set included patients first undergoing CCTA and then intravascular US within 3 months between June 2013 and December 2020 at one tertiary hospital. The development set was randomly assigned to training and validation sets at a 7:3 ratio. Diagnostic performance was assessed internally and externally from three tertiary hospitals using the area under the curve (AUC). The prognostic value of the RS for predicting MACE was evaluated in a prospective cohort with suspected coronary artery disease between April 2018 and March 2019. Multivariable Cox regression analysis was used to evaluate the RS and conventional anatomic plaque features (eg, segment involvement score) for predicting MACE. Results The RS development data set included 419 lesions from 225 patients (mean age, 64 years ± 10 [SD]; 68 men), while the prognostic cohort included 1020 lesions from 708 patients (mean age, 62 years ± 11; 498 men). Sixteen radiomic features, including two shape features and 14 textural features, were selected to build the RS. The RS yielded a moderate to good AUC in the training, validation, internal, and external test sets (AUC = 0.81, 0.75, 0.80, and 0.77, respectively). A high RS (≥1.07) was independently associated with MACE over a median 3-year follow-up (hazard ratio, 2.01; P = .005). Conclusion A coronary CT angiography-derived radiomic signature of coronary plaque enabled the detection of vulnerable plaques that were associated with increased risk for future adverse cardiac outcomes. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by De Cecco and van Assen in this issue.

Background. Oscillatory shear stress (OSS) disrupts endothelial homeostasis and promotes oxidative stress, which can lead to atherosclerosis. In atherosclerotic lesions, Toll-like receptor 4 (TLR4) is highly expressed. However, the molecular mechanism by which TLR4 modulates oxidative changes and the cell signaling transudation upon OSS is yet to be determined. Methods and Results. Carotid artery constriction (CAC) surgery and a parallel-plate flow chamber were used to modulate shear stress. The results showed that OSS significantly increased the oxidative burden, and this was partly due to TLR4 activation. OSS activated NOX2 and had no significant influence to NOX1 or NOX4 in endothelial cells (ECs). OSS phosphorylated caveolin-1, promoted its binding with endothelial nitric oxide synthase (eNOS), and resulted in deactivation of eNOS. TLR4 inhibition restored levels of nitric oxide (NO) and superoxide dismutase (SOD) in OSS-exposed cells. Conclusion. TLR4 modulates OSS-induced oxidative stress by activating NOX2 and suppressing eNOS.