3D automatic liver and spleen assessment in predicting overt hepatic encephalopathy before TIPS: a multi-center study.

BACKGROUND: Overt hepatic encephalopathy (HE) should be predicted preoperatively to identify suitable candidates for transjugular intrahepatic portosystemic shunt (TIPS) instead of first-line treatment. This study aimed to construct a 3D assessment-based model to predict post-TIPS overt HE. METHODS: In this multi-center cohort study, 487 patients who underwent TIPS were subdivided into a training dataset (390 cases from three hospitals) and an external validation dataset (97 cases from another two hospitals). Candidate factors included clinical, vascular, and 2D and 3D data. Combining the least absolute shrinkage and operator method, support vector machine, and probability calibration by isotonic regression, we constructed four predictive models: clinical, 2D, 3D, and combined models. Their discrimination and calibration were compared to identify the optimal model, with subgroup analysis performed. RESULTS: The 3D model showed better discrimination than did the 2D model (training: 0.719 vs. 0.691; validation: 0.730 vs. 0.622). The model combining clinical and 3D factors outperformed the clinical and 3D models (training: 0.802 vs. 0.735 vs. 0.719; validation: 0.816 vs. 0.723 vs. 0.730; all p < 0.050). Moreover, the combined model had the best calibration. The performance of the best model was not affected by the total bilirubin level, Child-Pugh score, ammonia level, or the indication for TIPS. CONCLUSION: 3D assessment of the liver and the spleen provided additional information to predict overt HE, improving the chance of TIPS for suitable patients. 3D assessment could also be used in similar studies related to cirrhosis.

Toxicity assessment and mechanistic investigation of engineered monoclinic VO2 nanoparticles.

Growing interest in monoclinic VO2 nanoparticles (NPs) among consumers and the industries of window coatings, solar sensors etc. has brought particular attention to their safety concerns. The toxicity of this new class of nanomaterials in bacterial ecosystems has not yet been evaluated. The degree of crystallinity is a significant parameter that determines the performance of materials. However, the previously reported methods for toxicity assessment have neglected its influence. In this work, we systematically evaluated the toxicity of VO2 NPs with different degrees of crystallinity to four typical bacterial strains and studied the influence of physicochemical properties and aging treatment on their antibacterial effect. The results showed that the toxicity of VO2 nanoparticles was very low. Interestingly, we found that antibacterial properties of VO2 NPs were dependent on both bacterial strains and VO2 particle properties. In addition, the highly crystalline VO2 NPs were more toxic than normal and industrial VO2 particles. We attribute the crystallinity-related toxicity to the dissolved vanadium, the physical interactions between the bacteria and particles, and the generation of reactive oxygen species, as supported by our experimental results and theoretical calculation.