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Acute pancreatitis (AP) is a common and serious acute inflammatory disease with high severity rate and mortality. Inflammation and oxidative stress play an extremely important role in the development of AP disease. Polyvinylpyrrolidone‐modified iridium nanoparticles (IrNP‐PVP) have multienzyme mimetic activity, and the aim of this article is to discuss the therapeutic alleviative effects of the ultrasmall nanozymes IrNP‐PVP on AP through their antioxidant and anti‐inflammatory effects. IrNP‐PVP were proved to inhibit inflammation and scavenge reactive oxygen species (ROS) at the cellular level. The synthetic IrNP‐PVP exhibit remarkable antioxidant and anti‐inflammatory activities in the prevention and treatment of AP mice by establishing murine AP model, which can reduce the oxidative stress and inflammatory response. The results of this article indicated that the ultrasmall nanozymes IrNP‐PVP effectively alleviate AP via scavenging ROS as well as suppressing inflammation both in vivo and in vitro, which might provide enormous promise for the AP management. [ABSTRACT FROM AUTHOR]

The quality of myrrh decoction pieces can be influenced by factors such as origin, source, and processing methods. The quality of myrrh in the market varies greatly, and adulteration is a serious issue, highlighting the urgent need for improved quality control measures. This study explores the integration of GC–MS analysis and sensor selection in electronic nose technology for the improved classification of myrrh decoction pieces. GC–MS analysis revealed the presence of 130 volatile compounds in the six myrrh samples, primarily composed of alkene compounds, and each sample exhibited variations in composition. An electronic nose system was designed using a sensor array consisting of six sensors selected from twelve sensors capable of detecting volatile compounds consistent with myrrh composition, including WO3 quantum dots, Fe2O3 hollow nanorods, ZnFe2O4 nanorods, SnO2 nanowires, and two commercially available sensors. The sensors exhibited distinct response patterns to the myrrh samples, indicating their suitability for myrrh analysis. Various sensor parameters, including response, response and recovery time, integral area, and slope, were computed to characterize the sensors' performance. These parameters provided valuable insight into the sensor–gas interactions and the unique chemical profiles of the myrrh samples. The LDA model demonstrated high accuracy in differentiating between the myrrh types, utilizing the discriminative features captured by the sensor array, with a classification accuracy of 90% on the testing set. This research provides a comprehensive evaluation method for the quality control of myrrh pieces and a scientific basis for the development and utilization of myrrh. [ABSTRACT FROM AUTHOR]