A deep genetic mystery has baffled plant scientists for decades. Although leaves, stems, and flowers develop in strikingly similar ways across many plant species, scientists have struggled to identify the shared DNA instructions that guide their formation. A new study now uncovers this hidden regulatory code and shows that its core has been conserved for 300 million years of plant evolution. Remarkably, these ancient DNA sequences were hidden in plain sight but were obscured by the constant reshuffling and duplication of plant genomes. By uncovering this deep-time blueprint, the research reshapes our understanding of plant evolution, showing how core regulatory logic is preserved and modified to guide the diversity of plant shapes and forms. The findings also carry important implications for agriculture, where fine-tuning gene regulation, rather than altering genes themselves, opens new paths to developing more resilient and productive crops.

A new AI-driven system generates plans for long-term, complex tasks about twice as well as some existing methods. The technique, developed at MIT, uses two vision-language models that work together to simulate actions and produce files for formal planning software.

A 25-year graph algorithm gap for the All Pairs Shortest Paths (APSP) problem has been narrowed by Dr Manoj Gupta, an Associate Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Gandhinagar. Previous methods provided distance estimates that were no worse than twice the actual distance (2-approximation) and worked effectively only for distant points. The new method, however, offers a reliable 2-approximation guarantee for the APSP problem while handling considerably closer spots with the same efficiency. This advance helps make large-scale network analysis faster and more practical across many real-world systems.