Core Insights - The article highlights significant advancements in various fields of research published in the journal Cell, with a notable contribution from Chinese scholars, indicating a strong presence in cutting-edge scientific research [1]. Group 1: Measles Virus Research - A study by Zhang Heqiao and Roger Kornberg's team elucidated the structure of the measles virus polymerase complex and its interaction with non-nucleoside inhibitors, laying the groundwork for rational antiviral drug design [3][4]. Group 2: AI in Protein Engineering - The research team led by Gao Caixia developed a novel AI protein engineering simulation method called AiCE, which integrates structural and evolutionary constraints, enabling efficient protein evolution simulation and functional design without the need for specialized AI model training [7]. Group 3: Vertebrate Genomics - The team from Zhejiang University introduced a high-throughput, sensitive single-nucleus ATAC sequencing technology (UUATAC-seq) to create chromatin accessibility maps, and developed the Nvwa model for predicting cis-regulatory elements, revealing the conserved syntax of vertebrate regulatory sequences [10][11]. Group 4: Primate Brain Research - A study identified cell type-specific enhancers in the macaque brain, establishing tools for understanding primate brain structure and diseases, which could enhance insights into cognitive functions [15]. Group 5: Peripheral Nerve Imaging - Researchers from the University of Science and Technology of China pioneered a high-speed, subcellular resolution imaging technique for whole-mouse peripheral nerves, providing a detailed peripheral nerve atlas and new tools for studying nerve regulation and disease mechanisms [19]. Group 6: Primate Prefrontal Cortex Connectivity - A study reconstructed the whole-brain connectivity network of the macaque prefrontal cortex at the single-neuron level, revealing refined axon targeting and arborization, which is crucial for understanding complex cognitive functions in primates [23]. Group 7: Optogenetics in Drug Discovery - The research led by Felix Wong developed an optogenetics platform for discovering selective modulators of the integrated stress response, identifying compounds that enhance cell death without toxicity, and demonstrating antiviral activity in a herpes simplex virus mouse model [27][28]. Group 8: Engineering Yeast Behavior - A study from Imperial College London established engineering principles for yeast, enabling programmable multicellular behaviors, transforming yeast from a "single-cell factory" to a "multicellular system chassis" [33][34].

Group 1 - Kunlun Wanwei released and open-sourced Skywork-R1V 3.0, achieving a score of 76.0 in the comprehensive multimodal evaluation MMMU, surpassing closed-source models like Claude-3.7-Sonnet (75.0) and GPT-4.5 (74.4), nearing the level of human junior experts (76.2) [1] - Hugging Face announced the release and open-sourcing of the small parameter model SmolLM3, which supports six languages and features a 128k context window, enabling deep and non-deep reasoning modes [1] - Zhejiang University developed a deep learning AI model named "Nuwa CE" for genomic prediction design, achieving over 90% accuracy in predicting phenotypic changes due to mutations in genomic regulatory regions, with results published in the journal Cell [1] Group 2 - Hugging Face's desktop robot Reachy Mini is now available for order, featuring two versions: Reachy Mini Wireless priced at $449 (approximately 3224 RMB) and Reachy Mini Lite at $299 (approximately 2147 RMB), both designed for developers [1][2] - Both versions of Reachy Mini are open-source DIY kits, comparable in size to a plush toy, equipped with screens and antenna structures, allowing users to program via Python and access over 1.7 million AI models and 400,000 datasets through the Hugging Face Hub [2]

Core Insights - The "Nüwa CE" deep learning AI model developed by Professor Guo Guoji's team at Jiang University can predict phenotypic changes due to mutations in genomic regulatory regions with over 90% accuracy [1][2] - The model is based on a high-throughput, high-sensitivity single-nucleus chromatin accessibility sequencing technology, creating a comprehensive regulatory element atlas covering five representative vertebrate species [1] - The model aims to enhance understanding of the complex regulatory language hidden within vast gene sequences, contributing to advancements in life sciences, medicine, and agriculture [1][2] Group 1 - The "Nüwa CE" model surpasses existing genomic AI models in multiple metrics, demonstrating its capability to predict phenotypic changes in various cell types following mutations in genomic regulatory elements [2] - The model has been applied to modify a therapeutic gene locus for sickle cell anemia, resulting in increased fetal hemoglobin expression [2] - The development of the model is part of a broader effort to decode the genetic information that remains largely unexplored, with less than 10% of the human genome's hereditary information deciphered [1]