Engineered microbe-based micro/nanorobots redefine interventional therapy for luminal cancers
Peer-Reviewed Publication
Updates every hour. Last Updated: 27-Oct-2026 08:16 ET (27-Oct-2026 12:16 GMT/UTC)
A new review in Medicine Plus outlines a transformative paradigm for luminal cancers using engineered microbe-based micro/nanorobots. Deployed via oral, suppository, or intracavitary routes, these living platforms bypass physiological barriers, colonize tumor niches, continuously synthesize therapeutics, and remodel the tumor microenvironment. Merging microbial adaptability with synthetic biology, they usher in an era of persistent, spatially controlled intervention.
A new review in Medicine Plus traces the evolution of mRNA lipid nanoparticles (mRNA-LNPs) from prophylactic vaccine vehicles to programmable therapeutic platforms. The authors detail clinical and preclinical progress across infectious disease, cancer, autoimmunity, rare genetic disease and tissue repair, while identifying key translational hurdles including extrahepatic targeting, repeat-dose immunogenicity, off-target editing risks, and scalable manufacturing.
This study analyzes 30 surface-water metagenomes from four functionally distinct waterbody types in Beijing, revealing starkly differentiated antibiotic resistance gene (ARG) landscapes. Urban rivers sustained the highest ARG burden, while relatively isolated urban lakes exhibited the lowest. Notably, receiving waters linked to the South-to-North Water Diversion Project maintained an intermediate load yet displayed the strongest coupling between ARGs and mobile genetic elements (R2=0.965), signaling elevated mobilization potential at these hydrological interfaces. The findings provide a foundational ecological framework for tracking resistance transport and informing risk-oriented management of megacity aquatic networks.
POSTECH researchers develop a new analytical framework that reveals hidden periodicity in complex metasurfaces.
- Professor Min-Soo Kim’s research team in the School of Computing develops SafeQL, a technology that identifies and selectively corrects errors in AI-generated SQL queries
- SafeQL resolves execution errors in up to 87.4% of initially erroneous queries in international benchmark tests, while reducing token use by a factor of up to 15.1 and correction time by a factor of up to 29.6 compared with full query regeneration
- The technology corrects references to nonexistent database tables, columns, functions, and values, helping reduce enterprise AI operating costs and advance reliable AI work assistants
NSF CAREER Awards will support two five-year research projects aimed at advancing cybersecurity and AI-guided electrochemical technologies. One project will develop privacy-protecting cybersecurity approaches for AI-enabled devices operating at the edge of networks, including wearable health monitors. The other will use AI to examine how small organic molecules influence catalytic reactions, with the goal of capturing carbon dioxide and converting it more efficiently into fuels and other valuable chemicals.