A Johns Hopkins Medicine-led research team has received an award of up to $52.1 million over four years from the Advanced Research Projects Agency for Health (ARPA-H), part of the Department of Health and Human Services, to better understand the rules that decide what shape a protein takes — and how those rules could support the identification of earlier diagnostics and therapeutic targets when proteins fold the wrong way. The team will start this work, which will be publicly shared through open-access resources, by studying Parkinson’s disease and Ewing sarcoma, a rare cancer of bone and soft tissue in children and young adults.

A new review published in PhotoniX Synergy examines how artificial intelligence is transforming the design of terahertz (THz) metamaterial devices (meta-devices). The authors survey conventional and AI-assisted approaches for THz meta-absorbers, modulators, filters, sensors, detectors, and multifunctional devices, and show how machine learning, evolutionary algorithms, deep learning, generative models, and large language models can establish data-driven links between structural geometry and electromagnetic response. The review also discusses challenges including computational cost, limited interpretability, data scarcity, and manufacturability, and outlines future directions such as physics-informed learning, multi-scale optimization, and AI-assisted optical computing hardware for 6G communication, imaging, biosensing, spectroscopy, and security inspection.

Artificial intelligence has already demonstrated great promise in many aspects of biomedical research, from accelerating scientific discovery to speeding the translation of biological insights into new therapies. Scripps Research today announced it has received a significant award of in-kind compute power from the Jen-Hsun and Lori Huang Foundation to advance the adoption of AI into biomedicine and help realize its potential. The grant, totaling more than 14 million hours of compute time, is provided through the Huang Foundation's partnership with CoreWeave using NVIDIA GPUs.

Frontiers’ AI in Science Enablers pledge opens today. The pledge includes AI-powered data curation for 1,000 Horizon Europe datasets and 100 FAIR2 Data Publication Grants for early-career researchers, helping turn research data into peer-reviewed, citable outputs that are better prepared for reuse and AI applications.

Electronic skin (e-skin), a stretchable, conformable, and multimodal sensing platform, is rapidly advancing in healthcare, robotics, and human–machine interaction (HMI). However, prolonged wear and sweat accumulation at the e-skin-skin interface can introduce signal artifacts, cause discomfort, and eventually lead to interfacial failure. Inspired by the unidirectional liquid transport of the Nepenthes peristome, we constructed an intelligent breathing e-skin (SPTL) featuring a Janus bilayer structure that creates a “liquid diode” effect for active sweat transport, achieving a remarkable cumulative one-way transport index of 956.36 while maintaining a dry interface even under profuse perspiration. This device exhibits a high tensile strain of 627%, a breathability of 20.02 mm s−1, and a pressure sensitivity of 7.39 kPa−1. Furthermore, the SPTL demonstrates versatile multimodal sensing capabilities, including real-time Morse code and non-contact capacitive sensing, while sustaining stable performance over 10,000 pressing cycles (capacitance decay < 3%). As a bio-integrated electrode, SPTL enables high-fidelity acquisition of electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG) signals, significantly outperforming commercial Ag/AgCl electrodes. Integrated with machine learning algorithms and EMG signals captured by the SPTL, it facilitates precise teleoperation of a quadruped robot and handwritten letter recognition with over 95% accuracy. This bionic strategy provides a versatile solution for intelligent, breathable, and multimodal bio-integrated interfaces.