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Inflammation is a key contributor to diabetic kidney disease pathogenesis, including reactive oxidation stress (ROS)‐mediated nuclear factor‐κB (NF‐κB) signaling pathway. In this study, we examined the effect of Astragaloside IV (AS‐IV) on anti‐inflammatory and anti‐oxidative properties under high glucose (HG) condition and the potential mechanism in glomerular mesangial cells (GMCs). We showed that AS‐IV concentration‐dependently reduced GMCs proliferation, restrained ROS release and hydrogen peroxide content, and suppressed pro‐inflammatory cytokines as well as pro‐fibrotic factors expression, which were associated with the inhibition of NF‐κB and nuclear factor‐erythroid 2‐related factor 2 (Nrf2) signaling activation. Accordingly, both NF‐κB overexpression by using RNA plasmid and Nrf2 gene silencing by using RNA interference weakened the ability of AS‐IV to ameliorate HG‐induced oxidative stress, inflammation, and cell proliferation. Furthermore, phosphatidylinositide 3‐kinases (PI3K)/serine/threonine protein kinase (Akt) and extracellular regulated protein kinases (ERK) signaling pathway regulated the process of AS‐IV‐induced Nrf2 activation and antioxidant capacity, which evidenced by using PI3K inhibitor LY294002 or ERK inhibitor PD98059 that largely abolished the AS‐IV efficacy. Taken together, these results indicated that AS‐IV protected against HG‐induced GMCs damage by inhibiting ROS/NF‐kB‐induced increases of inflammatory cytokines, fibrosis biomarkers, and cell proliferation via up‐regulation of Nrf2‐dependent antioxidant enzyme expression, which were mediated by PI3K/Akt and ERK signaling pathway activation. [ABSTRACT FROM AUTHOR]

Objective: To establish a classification model for the evaluation of rat fetal lung maturity (FLM) using radiomics technology. Method: A total of 430 high‐throughput features were extracted per fetal lung image from 134 fetal lung ultrasound images (four‐cardiac‐chamber views) of 67 Sprague–Dawley (SD) fetal rats with a gestational age of 16–21 days. The detection of fetal lung tissues included histopathological staining and the expression of surface proteins SP‐A, SP‐B, and SP‐C. A machine learning classification model was established using a support vector machine based on histopathological results to analyze the relationship between fetal lung texture characteristics and FLM. Results: The rat fetal lungs were divided into two groups: terminal sac period (SD1) and canalicular period (SD2). The mRNA transcription and protein expression level of SP‐C protein were significantly higher in the SD1 group than in the SD2 group (p < 0.05). The diagnostic performance of the rat FLM classification model was measured as follows: area under the receiver operating characteristic curve (AUC), 0.93 (training set) and 0.89 (validation set); sensitivity, 89.26% (training set) and 87.10% (validation set); specificity, 85.87% (training set) and 79.17% (validation set); and accuracy, 87.79% (training set) and 83.64% (validation set). Conclusion: Ultrasound‐based radiomics technology can be used to evaluate the FLM of rats, which lays a foundation for further research on this technology in human fetal lungs. Key points: What is already known about this topic? Recently, the combination of ultrasound images with artificial intelligence technology has provided a new idea for the detection of fetal lung maturity (FLM), while there is no gold standard to determine the validity of the results. What does this study add? The results of this study may lay an animal experimental foundation for the application of ultrasound‐based radiomics technology in the evaluation of human FLM. [ABSTRACT FROM AUTHOR]