Researchers from the University of Oxford have uncovered evidence that Mars once hosted enormous, Earth-like magmatic systems deep beneath its surface – despite the planet lacking the plate tectonics long thought necessary for this kind of geological complexity. The findings, published today (26 June) in Nature Astronomy, reveal fascinating new possibilities for how rocky planets become habitable.

Stanford researchers developed an AI tool that creates novel burger recipes optimized for individual preferences. The implications for science go well beyond food.

When the Göttingen anatomist Rudolf Wagner examined a brain in 1856 that was later mistakenly believed to be that of the famous mathematician Gauss, he noticed an unknown peculiarity: a connection above the central fissure — which separates two parts of the brain — that he described as a "bridge." Twenty years later, in 1876, the Viennese anatomist Richard Heschl searched more than 1,000 brains for further instances of this "bridge" and was able to identify it in six of them. He also measured an ordinary brain winding at the same location, situated at the base of the fissure, as he suspected a connection between this "deep winding" and the "bridge": if the deep-lying winding occurred at varying heights, the "bridge" should appear at the same location, but at the brain's surface. The data confirmed his hypothesis. 150 years later, researchers from the German Primate Center – Leibniz Institute for Primate Research (DPZ) and the University of Göttingen, led by Renate Schweizer, a scientist in the Department of Functional Imaging at the DPZ, have now replicated Heschl's findings. For their work, Renate Schweizer, together with her co-authors Anna M. Müllen and Julius Stropel, has been awarded the Replication Prize of the Organization for Human Brain Mapping. The article on which the prize is based was published in 2025 in the journal Brain Structure and Function.

New research from a University of Texas at Dallas professor considers how urban planners can design a city’s infrastructure around self-driving cars.

Histopathology is a cornerstone of clinical diagnosis, especially in cancer care. However, conventional chemical staining is often time-consuming and labor-intensive and may consume precious tissue samples. A cross-disciplinary research team at The Hong Kong University of Science and Technology (HKUST) has developed a novel generative AI (GenAI) framework that can produce high-fidelity virtually stained images even when training image pairs are imperfectly aligned, paving the way for faster and more tissue-saving histopathology workflows. The study titled “Generative AI for misalignment-resistant virtual staining to accelerate histopathology workflows” was recently published in the international journal Nature Communications.