The Volga region is one of the main grain-producing regions of Russia. Wheat stem rust caused by Puccinia graminis f. sp. tritici is among the most destructive fungal diseases of wheat. Recently, its harmfulness has increased in the Volga region. In this regard, an analysis of the resistance and diversity of the Sr genes in the Russian wheat cultivars is necessary. In this work, 126 wheat cultivars (including 23 durum wheat cultivars and 103 bread wheat cultivars) approved for use in the Volga region were evaluated for their resistance to two samples of P. graminis f. sp. tritici populations from different Volga region areas at the seedling stage. Specific DNA primers were used to identify resistance genes (Sr2, Sr24, Sr25, Sr26, Sr28, Sr31, Sr32, Sr36, Sr38, Sr39, and Sr57). Highly resistant cultivars (30 from 126) were identified. In bread wheat cultivars, the genes Sr31 (in 19 cultivars), Sr24 (in one cultivar), Sr25 (in 15 spring wheat cultivars), Sr28 (in six cultivars), Sr38 (in two cultivars), and Sr57 (in 15 cultivars) and their combinations—Sr31 + Sr25, Sr31 + Sr38, Sr31 + Sr28, Sr31 + Sr57, Sr31 + Sr28 + Sr57, and Sr31 + Sr24—were identified. The obtained results may be used to develop strategies for breeding rust-resistant cultivars.

The rapid and accurate detection of viral infections is of paramount importance, given their widespread impact across diverse demographics. Common viruses such as influenza, parainfluenza, rhinovirus, and adenovirus contribute significantly to respiratory illnesses. The pathogenic nature of certain viruses, characterized by rapid mutations and high transmissibility, underscores the urgent need for dynamic detection methodologies. Quantitative reverse transcription PCR (RT-qPCR) remains the gold-standard diagnostic tool. Its reliance on costly equipment, reagents, and skilled personnel has driven explorations of alternative approaches, such as catalytic DNA nanomachines. Diagnostic platforms using catalytic DNA nanomachines offer amplification-free nucleic acid detection without the need for protein enzymes and demonstrate feasibility and cost-effectiveness for both laboratory and point-of-care diagnostics. This study focuses on the development of multicomponent DNA nanomachines with catalytic proficiency towards a fluorescent substrate, enabling the generation of a fluorescent signal upon the presence of target nucleic acids. Specifically tailored variants are designed for detecting human parainfluenza virus type 3 (HPIV) and respiratory syncytial virus (RSV). The engineered DNA nanomachine features six RNA-binding arms for recognition and unwinding of RNA secondary structures, along with a catalytic core for nucleic acid cleavage, indicating potential utility in real clinical practice with minimal requirements. This research showcases the potential of DNA nanomachines as a reliable and sensitive diagnostic tool for RNA virus identification, offering promising prospects for clinical applications in the realm of infectious disease management.