与以往主要依据细胞类型划分的大脑图谱不同，新成果聚焦于脑区结构本身。它完全依托数据生成，边 界由细胞和分子特征自动界定，而非依赖人工经验判断。凭借对1300个脑区及亚区的精细划分，这张图 谱成为迄今动物脑中最精确、最复杂的数据驱动型图谱之一。 研究表明，CellTransformer不仅能准确再现海马体等已知脑区，还能在中脑网状核等理解不足的区域中 发现新的、更细分的亚区。 在人工智能（AI）与神经科学的强强联合下，美国加州大学旧金山分校与艾伦研究所团队联合开发出 一种名为CellTransformer的AI模型，助力绘制出目前最精细的小鼠脑图，共包含1300个脑区及亚区。这 一成果以前所未有的精细度揭示了大脑结构，使科学家得以将功能、行为和疾病状态与更小、更具体的 细胞区域相对应，为探索大脑工作机制开辟了新方向。相关成果发表于新一期《自然·通讯》杂志。 新模型的核心在于其Transformer架构，这与ChatGPT等大模型所采用的技术原理相同。研究人员称， Transformer模型擅长理解上下文关系，以往它用于分析句子中词语之间的联系，而CellTransformer则用 来分析空间中相邻细胞之间的关系 ...

以下文章来源于肥胖世界ObesityWorld ，作者肥胖世界 肥胖世界ObesityWorld . 《肥胖世界》Obesity World - 同步传真肥胖及代谢国际新学术进展，为医学减重临床、教研人员搭建一座与国际接轨的桥梁，「每医健」旗下内容平台。 研究团队构建了迄今最全面的脂肪组织单细胞图谱，涵盖171,247个细胞，样本来自25名极度肥胖者（术前及减重后）和24名健康瘦者，并结 合空间转录组数据（每组4人），聚焦与代谢异常紧密关联的腹部皮下脂肪。分析显示，肥胖脂肪组织中免疫细胞（尤其是巨噬细胞和淋巴细 胞）大量涌入，成熟脂肪细胞比例明显降低（暗示细胞死亡或更新不足）；而减重能有效缓解这些病理变化。 二、巨噬细胞的"记忆效应" 全球已有超10亿人被肥胖困扰。许多人以为"胖"仅是外表问题，殊不知腹部脂肪的异常实际上是代谢疾病的"隐形杀手"——它悄然引发胰岛素 抵抗、糖尿病、心血管疾病，甚至提高癌症风险。令人惊奇的是，减重能迅速扭转这些健康危机：血糖平稳了、血压下降了、血管恢复弹性 了。但科学界一直未能破解这一谜团：脂肪组织内部到底经历了什么变化？是细胞数量减少了？还是基因表达重新"洗牌"了？ 为揭开这一 ...

撰文丨王聪 编辑丨王多鱼 排版丨水成文 2025 年 10 月 1 日，国际顶尖学术期刊 Nature 上线了 18 篇论文 ， 其中 8 篇来自华人学者 （包括作为通讯作者和第一作者的论文） 。国际顶尖学术期刊 Cell 上线了 2 篇论文，这 2 篇均来自华人学者。 10 月 1 日，俄亥俄州立大学 李子海 教授 作为共同通讯作者 （ Wang Yi 为第一作者 ） ， 在 Nature 期刊发表了题为： Proteotoxic stress response drives T cell exhaustion and immune evasion （ 蛋白质毒性应激反应驱动 T 细胞衰竭和免疫逃逸 ） 的研究论文 【1】 。 10 月 1 日，麻省理工学院 Chi Fangtao 作为第一作者，在 Nature 期刊发表了题为： Dietary cysteine enhances intestinal stemness via CD8 T cell-derived IL-22 （ 饮食中的半胱氨酸通过 CD8 + T 细胞来源的 IL-22 增强肠道干细胞特性 ） 的研究论文 【2】 。 10 月 1 日 ...

来源：科技日报 图片由AI生成 ◎本报记者 张梦然 人们所知道的绝大多数关于植物的基本原理知识，都是在一种你可能从未听说过的植物——拟南芥中首 次发现的。 绘制植物的基因表达图谱 在作为模式植物的几十年间，拟南芥经历了无数实验。科学家们持续致力于解码其基因组，并绘制出不 同组织和器官中各类细胞的基因表达图谱。借助这些局部图谱，人们得以逐步揭示控制植物各部位身份 与功能的关键基因。 其中，单细胞RNA测序成为构建细胞图谱的核心工具。该技术不直接分析DNA，而是检测基因组的表 达产物——RNA分子，从而精准识别哪些基因在特定细胞中被激活，以及其表达水平的高低。由于生 物体所有细胞共享同一套遗传密码，细胞类型的区分依赖于其独特的基因表达模式，单细胞RNA测序 因此成为识别和分类细胞类型的有力手段。 然而，传统方法存在明显局限：科学家必须将组织解离为单个细胞，导致原本的空间结构被破坏。这意 味着虽然能获知"有哪些细胞"，却难以回答"它们在哪儿"以及"如何组织"。 为突破这一瓶颈，索尔克生物研究所团队将单细胞RNA测序与空间转录组学相结合，实现了从"碎片化 图谱"向"全景式地图"的跨越。 更先进技术带来更完整图谱 空间 ...

Core Insights - The article emphasizes the importance of understanding obesity through advanced scientific techniques, particularly single-nucleus RNA sequencing and spatial transcriptomics, which provide a detailed view of cellular changes in adipose tissue [6][7][12] Group 1: Research Findings - The study included three groups: 24 healthy individuals, and 25 obese individuals before and after weight loss surgery, revealing that weight loss surgery reduced the average BMI from 45.2 to 35.2, significantly improving fasting insulin and insulin resistance [7] - Analysis of over 170,000 cells identified more than 20 different cell states, showing a clear distinction in cellular organization between healthy and obese individuals, with a notable increase in macrophages in obese tissue [7][8] - In obese individuals, macrophages constituted 31% of adipose tissue, compared to 14% in healthy individuals, indicating a shift in immune cell dynamics [8] Group 2: Cellular Dynamics - The study identified two subtypes of lipid-associated macrophages (LAMs) in obese tissue: adaptive LAMs, which efficiently process lipids, and inflammatory LAMs, which are associated with insulin resistance [8][9] - The proportion of "stress-type" adipocytes in obese tissue was found to be 55%, which dropped to 14% post-weight loss, indicating a significant reduction in unhealthy adipocyte types [9][10] - The research linked obesity to cellular senescence, revealing that "stress-type" adipocytes express high levels of the senescence marker p21, which were largely eliminated after weight loss [10] Group 3: Implications for Treatment - The findings suggest that weight loss is not only about reducing fat but also involves a systemic cleansing of senescent cells, enhancing overall tissue health [12] - The persistence of inflammatory macrophages post-weight loss raises concerns about potential metabolic rebound, highlighting the need for preventive strategies [12] - The research provides insights into potential future treatments for obesity, focusing on targeting dysfunctional cells and signaling pathways rather than solely addressing energy balance [12]

Core Insights - The article emphasizes the importance of understanding obesity through advanced scientific techniques, particularly single-nucleus RNA sequencing and spatial transcriptomics, which provide detailed insights into cellular changes in adipose tissue [7][12]. Group 1: Research Methodology - The study involved three groups: 24 healthy individuals (LN group) and 25 obese individuals before and after weight loss surgery (OB and WL groups), allowing for both cross-sectional and longitudinal comparisons [8]. - The innovative "fat map" created through the research analyzed over 170,000 cells from 70 individuals, identifying more than 20 different cell states [8]. Group 2: Findings on Cellular Changes - Weight loss surgery significantly reduced the average Body Mass Index (BMI) from 45.2 to 35.2, with notable improvements in fasting insulin and insulin resistance [8]. - In healthy individuals, adipose tissue showed a well-organized community of cells, while in obese individuals, this balance was disrupted, particularly with an increase in macrophages and a decrease in mature adipocytes [8][9]. Group 3: Macrophage Dynamics - Macrophages in lean individuals constituted 14% of adipose tissue, while in obese individuals, this figure rose to 31%, with a notable presence of lipid-associated macrophages (LAMs) [9]. - LAMs were categorized into two subtypes: adaptive LAMs, which efficiently process lipids, and inflammatory LAMs, which are associated with insulin resistance [9]. Group 4: Adipocyte Changes - Analysis of over 44,000 mature adipocytes revealed a surge in unhealthy subtypes in obese tissue, including stress-type and fibrotic-type adipocytes, indicating functional failure of adipose tissue [10]. - Post-weight loss, the proportion of stress-type adipocytes dropped from 55% to 14%, indicating a significant reduction in stress and a potential for regeneration [10]. Group 5: Cellular Senescence - The study linked obesity to cellular senescence, identifying stress-type adipocytes as senescent cells expressing high levels of p21 [11]. - Weight loss effectively removed p21-positive senescent cells, leading to a decrease in harmful inflammatory factors, thus enhancing overall adipose tissue health [11]. Group 6: Implications for Future Treatments - The research highlights that weight loss is not just about reducing fat but also involves a systemic cleansing of senescent cells and restoration of tissue health [13]. - The findings suggest that future obesity interventions could focus on eliminating senescent cells or "re-educating" immune cells, moving beyond traditional energy balance models [13].

Core Viewpoint - The article discusses a significant advancement in understanding early organogenesis in mouse embryos through the creation of a 3D "digital embryo" using single-cell resolution techniques, which provides insights into organ formation and potential mechanisms of congenital malformations [2][10]. Group 1: Early Organogenesis - Early organogenesis is a critical phase in embryonic development characterized by extensive cell fate determination to initiate organ formation, while also being highly susceptible to developmental defects [4]. - At approximately day 7.5 of embryonic development (E7.5), mouse embryos undergo significant morphological changes, marked by the emergence of key structures such as the heart tube and primitive gut [4]. - The complex process of organ formation relies on precise cell migration, localization, and differentiation, regulated by spatiotemporal gene expression patterns and intricate signaling pathways [4][5]. Group 2: Research Methodology - The research team combined spatial transcriptomics methods (Stereo-seq) with cell segmentation techniques to analyze 285 continuous slices from six embryos at early organogenesis stages (E7.5-E8.0), generating a spatial transcriptomic map at single-cell resolution [6]. - A visualization platform named SEU-3D was developed to reconstruct the 3D "digital embryo," accurately reflecting gene expression patterns and cell states in the native embryonic environment [7]. Group 3: Findings and Implications - The research delineated spatial cell maps of endoderm and mesoderm derivatives, revealing complex signaling networks across germ layers and cell types [8]. - A region known as the progenitor determination zone (PDZ) was identified at the anterior interface of the embryo-extrembryonic region at E7.75, indicating coordinated signaling during heart progenitor formation [8]. - The results collectively establish a comprehensive spatiotemporal embryonic atlas at single-cell resolution, accompanied by a network-based exploration tool for navigating spatial gene expression and signaling networks, paving the way for deeper studies into embryonic development and diseases [10].

Core Insights - The research published by the National Medical Center of Hope City, USA, reveals the critical role of extrachromosomal DNA (ecDNA) in cancer evolution, providing a foundation for future precision medicine and personalized treatment options for cancer patients [1][2] Group 1: Research Findings - The study identifies the significant role of ecDNA, which has been previously overlooked, in driving cancer development and evolution [1] - New mechanisms of interaction between different ecDNAs have been uncovered, indicating that their presence alongside certain oncogenes can lead to a hypoxic tumor microenvironment, which is linked to cancer progression and treatment resistance [1][2] Group 2: Methodology and Applications - The research combines spatial transcriptomics and genomic data to identify distinct cell populations that have acquired additional mutations from a common ancestor, aiding in the understanding of tumor evolution [2] - The study focuses on glioma samples and establishes a comprehensive analytical framework that can be referenced by other research teams, with the potential for broader application in personalized cancer treatment [2]