Volatile organic compounds (VOCs) present in human exhaled breath have emerged as promising biomarkers for non-invasive disease diagnosis. However, traditional VOC detection technology that relies on large instruments is not widely used due to high costs and cumbersome testing processes. Machine learning-assisted gas sensor arrays offer a compelling alternative by enabling the accurate identification of complex VOC mixtures through collaborative multi-sensor detection and advanced algorithmic analysis. This work systematically reviews the advanced applications of machine learning-assisted gas sensor arrays in medical diagnosis. The types and principles of sensors commonly employed for disease diagnosis are summarized, such as electrochemical, optical, and semiconductor sensors. Machine learning methods that can be used to improve the recognition ability of sensor arrays are systematically listed, including support vector machines (SVM), random forests (RF), artificial neural networks (ANN), and principal component analysis (PCA). In addition, the research progress of sensor arrays combined with specific algorithms in the diagnosis of respiratory, metabolism and nutrition, hepatobiliary, gastrointestinal, and nervous system diseases is also discussed. Finally, we highlight current challenges associated with machine learning-assisted gas sensors and propose feasible directions for future improvement.

Antioxidants are substances that have the ability to resist or delay oxidative damage. Antioxidants can be used not only for the diagnosis and prevention of vascular diseases, but also for food preservation and industrial production. However, due to the excessive use of antioxidants, it can cause environmental pollution and endanger human health. It can be seen that the development of antioxidant detection technology is important for environment/health maintenance. It is found that traditional detection methods, including high performance liquid chromatography, gas chromatography, etc., have shortcomings such as cumbersome operation and high cost. In contrast, the nanozyme-based detection method features advantages of low cost, simple operation, and rapidity, which has been widely used in the detection of various substances such as glucose and antioxidants. This article focuses on the latest research progress of nanozymes for antioxidant detection. Nanozymes for antioxidant detection are classified according to enzyme-like types. Different types of nanozyme-based sensing strategies and detection devices are summarized. Based on the summary and analysis, one can find that the development of commercial nanozyme-based devices for the practical detection of antioxidants is still challenging. Some emerging technologies (such as artificial intelligence) should be fully utilized to improve the detection sensitivity and accuracy. This article aims to emphasize the application prospects of nanozymes in antioxidant detection and to provide new ideas and inspiration for the development of detection methods.

Alfalfa (Medicago sativa L.) is a crucial plant for saline and alkaline soil development, which is crucial for managing the salinization of global land resources. It can withstand saline and alkaline stress and can fix nitrogen. By secreting phytohormones, fixing nitrogen, and boosting antioxidant capacity, nitrogen–fixing bacteria, rhizobacteria, and other inter–root biotrophic bacteria encourage alfalfa development and reduce salinity stress. Alfalfa’s symbiotic association also encourages other plants to tolerate salinity and greatly boosts the amount of nitrogen in the soil. The mechanism by which inter–root growth–promoting bacteria mitigate saline and alkaline stress in alfalfa remains a prominent research focus. This paper reviews the current state of research on inter–root probiotic bacteria associated with alfalfa, utilizing literature mining to summarize the resource information of inter–root nitrogen–fixing bacteria found in saline–alkaline soils. We elucidate their nitrogen-fixing mechanisms and adaptive characteristics, explore their roles and potential applications in the improvement of saline–alkaline lands, and provide a theoretical foundation for the development of novel nitrogen–fixing bacterial fertilizers and restoration technologies for saline–alkaline environments.