A team at the Texas A&M Health Institute of Biosciences and Technology has developed an artificial intelligence-designed molecular switch that uses caffeine to rapidly separate engineered proteins inside living cells and trigger cellular responses on demand. The platform, called CODS, short for caffeine-operated dissociation system, could help scientists build safer and more controllable gene and cell therapies.

As health systems explore AI tools for vaccine communication, a new Penn-led randomized controlled trial offers a cautionary finding: Brief chatbot conversations can make vaccine-hesitant parents more willing to vaccinate their children against HPV, but they did not outperform standard public health materials. The effects of the written materials also persisted, while those of the chatbots faded. The researchers say the next step is to test AI as part of broader support systems that help families move from intention to action.

Using a novel simulation model based on machine learning, an international research team at GSI/FAIR has succeeded in gaining a deeper understanding of element formation in stellar events such as neutron star mergers. For the first time, the scientists used deep learning with a neural network to model the energy release during r-process nucleosynthesis in hydrodynamic simulations. The results are published in the journal Physical Review D.

Assessing the relationship between a person’s progesterone and estradiol levels at a given moment could help determine when they are in a biologically optimal state for learning and memory. This is the conclusion of a study led by ICREA researcher Raül Andero at the Institut de Neurociències of the Universitat Autònoma de Barcelona (INc-UAB), which found that the ratio between these two sex hormones measured in saliva can predict participants’ performance in a learning and memory task.

The oceans hide some of the most sophisticated solutions that nature has ever developed and are an inexhaustible source of inspiration for the robotics of the future as well. The Bioinspired Soft Robotics research unit, coordinated by Barbara Mazzolai, Associate Director for Robotics at the Istituto Italiano di Tecnologia (IIT – Italian Institute of Technology), has developed an octopus-inspired soft robotic arm that, thanks to the technology embedded in its artificial suction cups, is capable of sensing contact, estimating the intensity and direction of the applied force, and grasping objects autonomously, even in complex environments such as underwater settings.

A University of Manchester student has developed a powerful new ultra‑lightweight tool that can turn dark, noisy footage into clear, detailed and usable images.