Core Viewpoint - The article discusses the groundbreaking Stereo-cell technology in single-cell sequencing, which overcomes the limitations of traditional methods by enabling multi-modal integration, real-time monitoring, and high-throughput capabilities, thus providing a comprehensive understanding of cellular characteristics and dynamics [4][20]. Group 1: Technology Breakthroughs - Stereo-cell technology achieves multi-modal integration, allowing for the simultaneous capture of cellular morphology, transcriptomics, and protein characteristics, akin to taking a "3D photo" of cells [12][13]. - The technology utilizes high-density DNA nanoball arrays, enabling unbiased capture of hundreds to millions of cells without the physical limitations of traditional methods, thus ensuring accurate identification of rare cell populations [11][9]. - Stereo-cell supports in-situ dynamic monitoring of cells, capturing gene transcription activity changes and spatial-temporal information, which expands the boundaries of single-cell research [15][19]. Group 2: Collaborative Initiatives - The establishment of the "10 Billion Cells Alliance" aims to create a comprehensive cell atlas and decode the underlying principles of life, driving innovation in life sciences from data accumulation to intelligent technology applications [4][20]. - The technology is expected to significantly impact clinical molecular medicine, providing new avenues for patient care and treatment through enhanced cellular analysis [20][21]. Group 3: Future Prospects - Stereo-cell is positioned as a next-generation life data engine, with plans to develop a "three major cell universe database" encompassing life maps, disease maps, and disturbance response maps, inviting global research teams to collaborate [20][22]. - The technology is anticipated to facilitate a transition from billions to trillions of cells in analysis, enabling a comprehensive understanding of cellular fates and functions throughout life [20].

Core Viewpoint - The article discusses a groundbreaking study published in Nature by a team led by Academician Zhang Zemin, focusing on the concept of "cross-tissue cellular modules" and their role in multicellular coordination within human tissues, particularly in the context of cancer progression [2][16]. Group 1: Research Background - The study integrates single-cell transcriptomic data from 706 healthy samples across 35 human tissues, creating the most comprehensive cross-tissue single-cell atlas to date, covering 2.29 million cells [8][16]. - The research identifies significant differences in cellular composition across various healthy tissues, revealing 12 distinct cross-tissue cellular modules (CMs) with unique cellular compositions and distributions [9][16]. Group 2: Cellular Modules and Their Functions - The identified cellular modules include CM04, CM05, CM06, and CM09, which are abundant in primary and secondary immune organs, indicating their roles in immune cell production and maturation [10][13]. - Other modules, such as CM02 and CM03, are primarily found in the urinary system and gastrointestinal tract, while CM08 is enriched in barrier tissues like skin and mucosal surfaces, suggesting their specific functional roles [10][11]. Group 3: Spatial Dynamics and Aging - The study employs spatial transcriptomics to illustrate how these cellular modules are spatially organized within tissues, highlighting their functional roles in maintaining tissue homeostasis [14][16]. - Notably, the immune cell modules CM05 and CM06 exhibit contrasting temporal dynamics with aging, where CM05 increases while CM06 decreases, indicating their potential as biomarkers for age-related changes [14][16]. Group 4: Implications for Cancer Research - The research extends to the tumor microenvironment (TME), analyzing single-cell transcriptomic data from 1,062 clinical samples across 29 cancer types, identifying 91 cell subpopulations [15][16]. - It reveals a dual remodeling of cellular modules during tumor progression, where healthy tissue-specific modules are lost, and cancer-associated modules emerge, providing insights into the fundamental organizational principles of multicellular ecosystems in health and disease [15][16].