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Background As one typical cardiovascular disease, atherosclerosis severely endanger people’ life and cause burden to people health and mentality. It has been extensively accepted that oxidative stress and inflammation closely correlate with the evolution of atherosclerotic plaques, and they directly participate in all stages of atherosclerosis. Regarding this, anti-oxidation or anti-inflammation drugs were developed to enable anti-oxidative therapy and anti-inflammation therapy against atherosclerosis. However, current drugs failed to meet clinical demands. Methods Nanomedicine and nanotechnology hold great potential in addressing the issue. In this report, we engineered a simvastatin (Sim)-loaded theranostic agent based on porous manganese-substituted prussian blue (PMPB) analogues. The biomimetic PMPB carrier could scavenge ROS and mitigate inflammation in vitro and in vivo. Especially after combining with Sim, the composite Sim@PMPB NC was expected to regulate the processes of atherosclerosis. As well, Mn2+ release from PMPB was expected to enhance MRI. Results The composite Sim@PMPB NC performed the best in regulating the hallmarks of atherosclerosis with above twofold decreases, typically such as oxidative stress, macrophage infiltration, plaque density, LDL internalization, fibrous cap thickness and foam cell birth, etc. Moreover, H2O2-induced Mn2+ release from PMPB NC in atherosclerotic inflammation could enhance MRI for visualizing plaques. Moreover, Sim@PMPB exhibited high biocompatibility according to references and experimental results. Conclusions The biomimetic Sim@PMPB theranostic agent successfully stabilized atherosclerotic plaques and alleviated atherosclerosis, and also localized and magnified atherosclerosis, which enabled the monitoring of H2O2-associated atherosclerosis evolution after treatment. As well, Sim@PMPB was biocompatible, thus holding great potential in clinical translation for treating atherosclerosis. Graphic abstract

Stroke is the leading cause of neurological disability in humans. Middle cerebral artery occlusion (MCAO) followed by reperfusion is widely accepted to mimic stroke in basic medical research. Triptolide is one of the major active components of the traditional Chinese herb Tripterygium wilfordii Hook F, and has been reported to have potent antiinflammatory and immunosuppressive properties. Since its preclinical effects on stroke were still unclear, we decided to study the effects of Triptolide on focal cerebral ischemia/reperfusion injury in this study. The results showed that Triptolide treatment significantly attenuates brain infarction volume, water content, neurological deficits, and neuronal cell death rate, which were increased in the MCAO model rats. Immunohistochemistry was used to analyze the expression of glial fibrillary acidic protein (GFAP), Cyclooxygenase-2 (COX-2), inducible nitric oxide (iNOS), and NF-jB in the ischemic brains. The administration of Triptolide showed down-regulation of the iNOS, COX-2, GFAP, and NF-jB expression in MCAO rats. It also increased the expression of bcl-2, and suppressed levels of bax and caspase-3 compared with the MCAO group. Our findings revealed that Triptolide exerts its neuroprotective effects against inflammation with the involvement of inhibition of NF-jB activation.

Background: The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is affected by low diagnostic specificity. Machine learning (ML) methods can optimize the diagnostic performance in medical image analysis. However, it is unknown which ML-based diagnostic pattern is more effective in improving diagnostic performance for thyroid nodules and reducing nodule biopsies. Therefore, we compared ML-assisted visual approaches and radiomics approaches with ACR TI-RADS in diagnostic performance and unnecessary fine-needle aspiration biopsy (FNAB) rate for thyroid nodules. Methods: This retrospective study evaluated a data set of ultrasound (US) and shear wave elastography (SWE) images in patients with biopsy-proven thyroid nodules (‡1 cm) from the Shanghai Tenth People's Hospital (743 nodules in 720 patients from September 2017 to January 2019) and an independent test data set from the Ma'anshan People's Hospital (106 nodules in 102 patients from February 2019 to April 2019). Six US features and five SWE parameters from the radiologists' interpretation were used for building the ML-assisted visual approaches. The radiomics features extracted from the US and SWE images were used with ML methods for developing the radiomics approaches. The diagnostic performance for differentiating thyroid nodules and the unnecessary FNAB rate of the ML-assisted visual approaches and the radiomics approaches were compared with ACR TI-RADS. Results: The ML-assisted US visual approach had the best diagnostic performance than the US radiomics approach and ACR TI-RADS (area under the curve [AUC]: 0.900 vs. 0.789 vs. 0.689 for the validation data set, 0.917 vs. 0.770 vs. 0.681 for the test data set). After adding SWE, the ML-assisted visual approach had a better diagnostic performance than US alone (AUC: 0.951 vs. 0.900 for the validation data set, 0.953 vs. 0.917 for the test data set). When applying the ML-assisted US+SWE visual approach, the unnecessary FNAB rate decreased from 30.0% to 4.5% in the validation data set and from 37.7% to 4.7% in the test data set in comparison to ACR TI-RADS. Conclusions: The ML-assisted dual modalities visual approach can assist radiologists to diagnose thyroid nodules more effectively and considerably reduce the unnecessary FNAB rate in the clinical management of thyroid nodules.