Improving T cell responses to vaccines
Peer-Reviewed Publication
Updates every hour. Last Updated: 7-Jun-2025 08:09 ET (7-Jun-2025 12:09 GMT/UTC)
A new AI tool to predict the spread of infectious disease outperforms existing state-of-the-art forecasting methods.
The tool, created with federal support by researchers at Johns Hopkins and Duke universities, could revolutionize how public health officials predict, track and manage outbreaks of infectious diseases including flu and COVID-19.
Researchers have developed a portable diagnostic system that evaluates an individual’s antibody protection against COVID-19 using just one microliter of fingertip blood. The Tip Optofluidic Immunoassay (TOI) combines high-sensitivity chemiluminescence detection with microfluidic biosensing to assess antibody protection from both pathogen binding and virus inhibition perspectives—all in just 40 minutes. While many platforms measure antibody levels, few capture the functional aspect of immunity: neutralization. TOI incorporates a renovated in vitro inhibition assay (RIVIA), enhanced through rational protein design to achieve high sensitivity and reproducibility. Unlike conventional methods that require large blood volumes and centralized lab facilities, TOI enables comprehensive immune profiling with minimal resources. Validated in over 100 volunteers, the platform shows strong potential for both public health surveillance and personalized immune assessment. This innovation bridges the gap between laboratory diagnostics and real-world healthcare, offering a practical tool for monitoring vaccine effectiveness and tracking immunity against emerging viral variants.
A study by Stanford University and the Institute for Bioengineering of Catalonia describes an innovative technology that enables the large-scale analysis of antibodies in biological samples. Using microscopic beads marked with stable isotopes, this advance surpasses traditional techniques, accelerating the study of immune responses and opening up new possibilities for biomedical research.
A new county-level dataset from Johns Hopkins University researchers reveals a national decline in the measles-mumps-rubella (MMR) vaccination rate among U.S. children since the start of the COVID-19 pandemic. Out of 2,066 studied counties, 1,614 counties, 78%, reported drops in vaccinations and the average county-level vaccination rate fell 93.92% pre-pandemic to 91.26% post-pandemic—an average decline of 2.67%, moving further away from the 95% herd immunity threshold to predict or limit the spread of measles.