Researchers explored how machine learning and quantum computing can be used to improve early detection of chronic kidney disease, aiming to develop faster, more accurate diagnostic tools for clinicians.

Artificial photosynthesis is highly desired to enhance natural photosynthesis through enhanced photoelectron transfer from photocatalysts to natural photosystems. Graphitic carbon nitride (g-C₃N₄ or CN), a biocompatible organic polymer semiconductor, has emerged as a promising candidate for boosting natural photosynthesis, paving the way for sustainable agricultural technologies to increase crop yields.

Myocardial ischemia/reperfusion injury (MI/RI) remains a major therapeutic challenge in acute myocardial infarction due to the lack of effective treatment options. Although mesenchymal stromal cells (MSCs) and their derivatives have shown promise in cardiac repair, their clinical translation is limited by poor delivery efficiency and reduced bioactivity. In this study, researchers developed nanoscale artificial cell-derived vesicles (Rg1-ACDVs) via mechano-extrusion of MSCs preconditioned with ginsenoside Rg1, a bioactive phytochemical. Compared to conventional extracellular vesicles (Rg1-EVs) and unprimed ACDVs, Rg1-ACDVs demonstrated superior therapeutic performance by promoting cell cycle progression and facilitating DNA damage repair, as revealed by multi-omics analyses. Functional assays confirmed their dual ability to scavenge reactive oxygen species (ROS) and safeguard genomic stability in both in vitro and in vivo models. This work underscores the synergistic potential of phytochemical priming and nanoscale bioengineering, establishing Rg1-ACDVs as a scalable and effective platform for advancing MI/RI therapy toward clinical application.