This paper presents quantitative analysis of blood flow shear stress by measuring the carotid arterial wall shear stress (WSS) and the intima-media thickness (IMT) of experimental rabbits fed with high-fat feedstuff on a weekly basis in order to cause atherosclerosis. This study is based on establishing an atherosclerosis model of high-fat rabbits, and measuring the rabbits’ common carotid arterial WSS of the experimental group and control group on a weekly basis. Detailed analysis was performed by using WSS quantification. We have demonstrated small significant difference of rabbit carotid artery WSS between the experimental group and the control group (P<0.01) from the 1st week onwards, while the IMT of experimental group had larger differences from 5th week compared with the control group (P<0.05). Next, we have shown that with increasing blood lipids, the rabbit carotid artery shear stress decreases and the rabbit carotid artery IMT goes up. The decrease of shear stress appears before the start of IMT growth. Furthermore, our receiver operator characteristic (ROC) curve analysis showed that when the mean value of shear stress is 1.198 dyne/cm2, the rabbit common carotid atherosclerosis fatty streaks sensitivity is 89.8%, and the specificity is 81.3%. The area under the ROC curve is 0.9283. All these data goes to show that WSS decreasing to 1.198 dyne/cm2 can be used as an indicator that rabbit common carotid artery comes into the period of fibrous plaques. In conclusion, our study is able to find and confirm that the decrease of the arterial WSS can predict the occurrence of atherosclerosis earlier, and offer help for positive clinical intervention.

Photothermal therapy (PTT) is an emerging technology as a noninvasive therapeutic modality for inducing photonic cancer hyperthermia. However, current photothermal conversion agents suffer from low therapeutic efficiency and single functionality. Engineering crystal defects on the surface or substrate of semiconductors can substantially enhance their optical absorption capability as well as improve their photothermal effects in theranostic nanomedicines. In this study, a specific defect engineering strategy was developed to endow two-dimensional (2D) BiOCl nanosheets with intriguing photothermal conversion performance by creating oxygen vacancies on the surface (O-BiOCl). Importantly, the photothermal performance and photoacoustic imaging capability of the 2D O-BiOCl nanosheets could be precisely controlled by modulating the amounts of oxygen vacancies. The strong Bi-based X-ray attenuation coefficient endowed these nanosheets with the contrast-enhanced computed tomography imaging capability. The high near-infrared-triggered photonic hyperthermia for tumor ablation was systematically demonstrated both in vitro at the cellular level and in vivo for tumor breast cancer mice xenograft models. Based on the demonstrated high biocompatibility of these 2D O-BiOCl nanosheets, this work not only formulates an intriguing 2D photothermal nanoagent for tumor ablation, but also provides an efficient strategy to control the photothermal performance of nanoagents by defect engineering.

Macrophage pyroptosis has been identified as a critical pathological mechanism in inflammation-related atherosclerosis (AS). In this work, we have demonstrated that Zn ²⁺ features the strongest anti-inflammatory performance by screening 10 representative metal ions, and the MTC1 agonists can trigger lysosomal Zn ²⁺ release and inhibit pyroptosis in macrophages. Based on these findings, we further engineered a mucolipin TRP channel 1 (MTC1)–related therapeutic nanoplatform for endogenously triggering lysosomal zinc release to curb inflammation and block macrophage pyroptosis. This nanoplatform consists of mesoporous silica nanoparticles to deliver MTC1 agonists and carbon nanodots, which could synergistically exert antiatherosclerotic effect by scavenging toxic reactive oxygen species, inhibiting macrophage pyroptosis, modulating macrophage transition, and rebuilding atherosclerotic immune microenvironment. These findings demonstrate that macrophage pyroptosis can be efficiently blocked via leveraging self-lysosomal zinc pool, which provides the paradigm of lysosomal zinc modulation-involved nanotherapeutics for managing other inflammatory diseases.

Background: Transthoracic echocardiography (TTE) is widely used in clinics to evaluate left ventricular hypertrophy (LVH). However, TTE is usually insufficient for the etiological diagnoses when morphological and functional features are nonspecific. With the booming of computer science and artificial intelligence (AI), previous literature has reported the application of radiomics based on cardiac magnetic resonance imaging, cardiac computed tomography and TTE in diagnosing several myocardial abnormalities, such as myocardial infarction, myocarditis, cardiac amyloidosis, and hypertrophic cardiomyopathy (HCM). In this study, we explored the possibility of using myocardial texture features in differentiating HCM, hypertensive heart disease (HHD) and uremic cardiomyopathy (UCM) based on echocardiography. To our knowledge, this was the first study to explore TTE myocardial texture analysis for multiple LVH etiology differentiation. Methods: TTE images were reviewed retrospectively from January 2018 to collect 50 cases for each group of HHD, HCM and UCM. The apical four chamber view was retrieved. Seventeen first-order statistics and 60 gray level co-occurrence matrix (GLCM) features were extracted for statistics and classification test by support vector machine (SVM). Results: Of all the parameters, entropy of brightness (EtBrt), standard deviation (Std), coefficient of variation (CoV), skewness (Skew), contrast7 (Cont7) and homogeneity5 (Hm5) were found statistically significant among the three groups (all P0.50). As a result, HCM showed the most homogeneous myocardial texture, and was significantly different from HHD and UCM (all six features: P≤0.005). HHD appeared slightly more homogeneous than UCM, as only EtBrt and CoV were significant (P=0.011 and P=0.008). According to higher areas under the receiver operating characteristic curve (AUC) (>0.50), EtBrt, Std, and CoV were selected for test of classification as a combination of features. The AUC derived from SVM model was slightly improved compared with those of EtBrt, Std and CoV individually. Conclusions: AI-based myocardial texture analysis using ultrasonic images may be a potential approach to aiding LVH etiology differentiation.