Elena Colicino

A Multi-Stage Deep Learning Framework for Daily PM2.5 Estimation at 100 m Resolution Across the Contiguous United States, 2000–2024 (A Quarter Century of Data)

Abstract Accurate high-resolution estimation of fine particulate matter (PM2.5) remains challenging because of sparse monitoring networks and missing satellite observations. We developed a multistage deep learning framework to generate daily PM2.5 concentrations at 100 m resoluti...

Susceptible perinatal windows to arsenic exposure and serum antibody levels in children

Several cohorts have documented potential immunotoxic effects of arsenic in pediatric populations, however, the identification of susceptible windows to arsenic exposure remains poorly investigated in relation to vaccine-specific antibody responses. The present study examines per...