Ginkgo Datapoints has launched the Virtual Cell Pharmacology Initiative (VCPI), an open-source effort to create the first standardized framework for virtual cell modeling in drug discovery. By offering free high-throughput RNA profiling and building a shared reference cell line, VCPI aims to generate more than 12 billion high-quality pharmacology data points and test at least 100,000 compounds. The initiative invites researchers and companies to contribute compounds, shape dataset priorities, and accelerate the development of predictive AI models for drug discovery.

Scientists from the University of Groningen in the Netherlands have developed a soft polymer hydrogel that can conduct electricity as well as metal can. This finding has the potential for a large numbers of applications, for example in biocompatible sensors and in wound healing.

Researchers have developed a new algorithm that combines two processes for personalizing robotic prosthetic devices to both optimize the movement of the prosthetic limb and – for the first time – also help a human user’s body engage in a more natural walking pattern. The new approach can be used to help restore and maintain various aspects of user movement, with the goal of addressing health challenges associated with an amputation.

Dance is a form of cultural expression that has endured all of human history, channeling a seemingly innate response to the recognition of sound and rhythm. A team at the University of Tokyo and collaborators demonstrated distinct fMRI activity patterns in the brain related to a specific audience’s level of expertise in dance. The findings were born from recent breakthroughs in dance motion-capture datasets and AI generative models, facilitating a cross-modal study characterizing the art form’s complexity.

Researchers from Aalto University used network theory to develop a method for measuring the impact of individuals on societal division. While the method can be applied to any case around which social media data can be gathered, the initial study utilised Twitter data collected before Finland’s 2019 and 2023 parliamentary elections. The results reveal how a relatively small elite can have a disproportionately large influence on shaping polarizing environments.

A geomagnetic superstorm is an extreme space weather event that occurs when the Sun releases massive amounts of energy and charged particles toward Earth. These storms are rare, occurring about once every 20-25 years. On May 10-11, 2024, the strongest superstorm in over 20 years, known as the Gannon storm or Mother’s Day storm, struck Earth.  

A study led by Dr. Atsuki Shinbori from Nagoya University's Institute for Space-Earth Environmental Research has captured direct measurements of this extreme event and provided the first detailed observations of how a superstorm compresses Earth's plasmasphere—a protective layer of charged particles that encircles our planet. Published in Earth, Planets and Space, the findings show how the plasmasphere and ionosphere react during the most violent solar storms and help forecast disruptions to satellites, GPS systems, and communication networks during extreme space weather events. 

The poplar (Populus alba) has a unique survival strategy: when exposed to hot and dry conditions, it curls its leaves to expose the ventral surface, reflecting sunlight, and at night, the moisture condensed on the leaf surface releases latent heat to prevent frost damage. Plants have evolved such intricate mechanisms in response to dynamic environmental fluctuations in diurnal and seasonal temperature cycles, light intensity, and humidity, but there have been few instances of realizing such a sophisticated thermal management system with artificial materials. Through this research, the KAIST research team has developed an artificial material that mimics the thermal management strategy of the poplar leaf, significantly increasing the applicability of power-free, self-regulating thermal management technology in applications such as building facades, roofs, and temporary shelters.

The growing complexity of wastewater treatment models often makes it difficult for researchers, engineers, and students to develop, validate, and apply these essential tools. To bridge this gap, a team from China has developed the Simplified Intelligent Modelling Platform Online (SIMPO), a free, open-source, cloud-native platform. SIMPO eliminates the need for coding through an intuitive drag-and-drop interface, integrates automatic error correction mechanisms and powerful simulation algorithms, and promotes collaboration through open sharing of models and data. By making advanced modelling accessible, SIMPO accelerates research, enhances engineering design, and supports education, directly contributing to UN Sustainable Development Goal 6 (Clean Water and Sanitation).