A National Science Foundation grant will help University of Delaware researchers create more secure computer chips by using AI and other tools to predict and counter hardware threats early in design.

In bustling megacities worldwide, smart trains and railways are emerging as heroes in the fight against gridlocked traffic and choking pollution. Powered by cutting-edge tech like IoT and digital connectivity, these systems promise faster, greener, and more personalized travel—think seamless real-time updates and automated operations. Yet, this digital evolution brings a dark side: heightened vulnerability to cyberattacks that could derail operations, compromise passenger safety, or expose sensitive data. As railways go "smart," the need for robust cybersecurity isn't just a tech add-on—it's essential to unlock the full potential of a connected world without inviting chaos. This study dives into the cybersecurity maze of smart railways, mapping out threats, vulnerabilities, and defenses to ensure these vital infrastructures remain resilient in an increasingly hostile digital landscape.

Los Angeles, CA – November 14, 2025 -   The Terasaki Institute for Biomedical Innovation (TIBI) is pleased to announce its collaboration with the California Institute of Technology (Caltech) on a newly awarded $2.8 million Discovery Stage Research (DISC0) grant from the California Institute for Regenerative Medicine (CIRM).

Researchers have announced the rediscovery of Moema claudiae, a species of seasonal killifish in Bolivia that was previously thought to be possibly extinct. This rediscovery provides new hope for the conservation of this unique fish and the diverse wetland habitats of the region.

MendelR is a fully automated R package specifically developed for Mendelian randomization (MR) studies, designed to address the technical challenges of causal inference in biomedical research. As a powerful causal inference method, Mendelian randomization can effectively reduce confounding bias in observational studies. However, its complex data processing workflow, diverse analytical approaches, and stringent hypothesis-testing requirements often deter researchers. MendelR integrates the latest eQTL and pQTL databases, along with multi-omics resources, to provide a one-stop solution covering data acquisition, preprocessing, and instrumental variable selection, through to various MR analysis methods, thereby significantly lowering the technical barriers to research. This toolkit supports not only standard two-sample MR analysis but also encompasses advanced applications, including mediation analysis, multivariate MR, drug target analysis, and multi-omics integration. It also incorporates rigorous sensitivity analyses and multiple-testing correction mechanisms to ensure the reliability of research findings. With its user-friendly interface, fully automated workflow, and diverse visualization features, MendelR offers an efficient and accurate MR analysis platform for researchers at all levels, from beginners to seasoned professionals, thereby advancing the in-depth development of causal relationship research in the biomedical field.