‘Nature’s algorithm’ found in Chinese money plants
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Jun-2026 22:15 ET (24-Jun-2026 02:15 GMT/UTC)
CSHL Associate Professor Saket Navlakha and former graduate student Cici Zheng have discovered a naturally occurring Voronoi diagram in Chinese money plants’ leaves. Their research answers a longstanding question in biology regarding the mathematics of looping vein structures and could help explain how plants solve complex problems in nature.
Targeted protein degradation has become one of the most promising strategies in modern drug discovery, enabling scientists to eliminate disease-causing proteins instead of merely blocking them. Now, researchers at CeMM, AITHYRA (both Institutes of the Austrian Academy of Sciences), and CeTPD have discovered that a single small molecule can recruit not one, but two independent protein disposal systems at the same time. This dual mechanism introduces a built-in redundancy that could make future degrader therapies more robust and less vulnerable to resistance. The findings, reported in Nature Chemical Biology (DOI: 10.1038/s41589-026-02224-y), expand the design principles of targeted protein degradation and open new avenues for more resilient medicines.
Researchers from The University of Osaka found that the zinc finger proteins RLF and ZFP292 play redundant roles in stabilizing the CoREST corepressor complex at gene promoters in embryonic stem cells. Deleting both proteins allowed the cells to differentiate, suggesting that they could be useful targets for maintaining stem cell quality.
The Nuffield Council on Bioethics (NCOB) says there is a clear need for guidance on how to conduct ethical research using neural organoids, warning that governance gaps reflect wider weaknesses in the UK’s outdated regulatory ecosystem which could hinder scientific progress.
For decades, the search for life beyond Earth has revolved around a key question: What molecules should scientists be looking for on other planets or moons? A new study suggests the more revealing clue may not be the molecules themselves, but the hidden order connecting them.
Scientists at the Stowers Institute for Medical Research and Helmholtz Munich have developed RegVelo, a new AI framework that predicts how cells acquire their identities and identifies the genetic regulators guiding those changes. Published in Cell, the study used zebrafish neural crest development to show RegVelo can uncover early drivers of cell fate, including regulators of pigment cell formation, and then support those predictions experimentally. The researchers also applied the framework across multiple biological systems, suggesting its value extends beyond neural crest cells as a broadly useful tool for studying how cells change over time. The team says the new model could pave the way for future cell therapy treatments.
Researchers develop light-induced Asp(D)-to-Ala(A) protein editors (LIDAPEs) which enable site-specific residue editing of endogenous protein in living cells, and lay the foundation for a new class of chemical biology tools.