Respiratory viruses that have diverse strains and mutate rapidly, such as influenza and COVID-19, are difficult to block perfectly with vaccines alone. To solve this problem, KAIST's research team has successfully developed a nasal (intranasal) antiviral platform using AI technology to overcome the existing limitations of interferon-lambda treatments—namely, being "weak against heat and disappearing quickly from the nasal mucosa."

KAIST announced on December 15th that a joint research team—consisting of Professor Ho Min Ktim and Professor Hyun Jung Chung from the Department of Biological Sciences, and Professor Ji Eun Oh from the Graduate School of Medical Science and Engineering used AI to stably redesign the interferon-lambda protein and combined it with a delivery technology that ensures effective diffusion and long-term retention in the nasal mucosa, thereby implementing a universal prevention technology for various respiratory viruses.

A University of Maryland, Baltimore County (UMBC) study, published in Nature Communications, uncovers how enteroviruses—including those causing polio, myocarditis, encephalitis, and the common cold—hijack host cell machinery to replicate. Researchers determined the structure of a cloverleaf-shaped RNA element in the viral genome bound to the viral protein 3CD, which recruits host factors to form the viral replication complex. 3CD also acts as a switch between genome copying and protein synthesis. This highly conserved mechanism across all seven enteroviruses in the study presents a stable target for developing broad-spectrum antiviral drugs that could disrupt this essential interaction and prevent replication.

Simulations of Turin, Milan and Palermo reveal that individual behaviour affects the intensity and timing of epidemics spreading in urban areas.