Core Insights - The article discusses a significant research paper published in the journal Cell, focusing on the genome sequences of extant and extinct gibbons, which provides insights into their phylogeny, demographic history, and conservation status [3][7]. Group 1: Research Findings - The research team conducted large-scale genome sequencing and comparative analysis of 18 extant gibbon species and mitochondrial genomes of 3 extinct gibbon samples, including the Junzi gibbon [6][7]. - The study clarified the evolutionary relationships among the four genera of gibbons, resolving a long-standing debate in academia regarding their classification [7]. - The extinct Junzi gibbon was reclassified under the Nomascus genus, negating its previous status as an independent genus [7][9]. Group 2: Genetic Insights - The research identified a deletion of 205 base pairs in the Sonic Hedgehog (SHH) gene, which is linked to the elongated limbs characteristic of gibbons [8][9]. - The historical dynamics of gibbon population sizes and habitat suitability were found to correlate with past climate changes, providing valuable information for conservation efforts [7][9]. Group 3: Implications for Conservation - The findings advance the understanding of gibbon evolution, biology, and conservation efforts, highlighting the importance of genomic studies in informing conservation strategies for threatened gibbon species [11].

Core Viewpoint - The research introduces a novel multimodal vision-language model named AFLoc (Annotation-Free pathology Localization), which enables automatic localization of pathologies in medical images without the need for prior annotations from doctors, showcasing strong generalization capabilities that surpass human benchmarks in various pathology image tasks [4][9]. Group 1 - AFLoc is designed to perform pathology localization without requiring annotations, thus reducing the dependency on expert input [4][10]. - The model utilizes a contrastive learning approach based on a multi-level semantic structure, aligning diverse medical concepts with rich image features to adapt to the varied manifestations of pathologies [7][9]. - Initial experiments were conducted on a dataset of 220,000 pairs of chest X-ray images and reports, demonstrating that AFLoc outperforms current state-of-the-art methods in both localization and classification tasks without annotations [9]. Group 2 - The research validates AFLoc's generalization capabilities across different modalities, including histopathology and retinal fundus images, indicating its robustness in diverse clinical environments [9][10]. - The findings highlight AFLoc's potential to lower annotation requirements and adapt to complex clinical applications, making it a significant advancement in the field of medical imaging [10].

Core Viewpoint - Perovskite solar cells are gaining attention due to their high efficiency, simple manufacturing process, and low cost, but the heat annealing process can induce crystal defects that limit their performance and stability [2][4]. Group 1: Research Findings - A new solid-state Molecular Press Annealing (MPA) strategy has been proposed, which involves imprinting a dense layer of pyridine-based molecular template on the perovskite surface during the heat annealing process, allowing for real-time repair of iodine vacancies and stabilization of the lead-iodine framework [5][6]. - The MPA strategy enhances the structural integrity and long-term stability of perovskite films, addressing the limitations caused by traditional heat annealing [5]. Group 2: Performance Metrics - The n-i-p structured perovskite solar cells fabricated using the MPA strategy achieved a power conversion efficiency (PCE) of 26.6% for small area devices (0.08 cm²) and 24.9% for 1 cm² devices, maintaining 23.0% efficiency for 16 cm² modules [7]. - The devices demonstrated exceptional durability, retaining 98.6% and 97.2% of their initial efficiency after 1617 hours of continuous operation at maximum power point and 5280 hours of atmospheric storage, respectively [7].

Core Viewpoint - CAR-T cell therapy has shown transformative success in hematological malignancies but faces challenges in solid tumors due to immunosuppressive tumor microenvironments and antigen heterogeneity [3][7]. Group 1: Challenges in CAR-T Cell Therapy - The main challenges in treating solid tumors with CAR-T cell therapy include the immunosuppressive tumor microenvironment and antigen expression heterogeneity [7]. - Antigen loss or escape during treatment often leads to off-target effects and resistance to CAR-T cells [3]. Group 2: Innovative Solutions - A research team from Harbin Medical University developed a platform called BROAD-CAR, which utilizes engineered outer membrane vesicles (OMV) to enhance CAR-T cell therapy for solid tumors [4][9]. - OMV can induce strong immune responses and alter the immunosuppressive tumor microenvironment without the risks associated with live bacteria [7]. Group 3: Mechanism and Efficacy - The BROAD-CAR platform enhances CAR-T cell anti-tumor activity by blocking the PD-1/PD-L1 signaling pathway, improving CAR-T cell expansion, and facilitating in situ antigen modification [9]. - In mouse models of breast cancer, BROAD-CAR has been shown to inhibit tumor recurrence and metastasis [9]. Group 4: Overall Implications - This research presents a safe and effective method to enhance the efficacy and applicability of CAR-T cell therapy in solid tumors [11].

撰文丨王聪 编辑丨王多鱼 排版丨水成文 反复自然流产 （RSA） 发生率约为 2% ，作为一种常见的 不良妊娠结局， 不仅严重影响适龄女性的生殖 健康，更给家庭带来沉重的心理压力和情感创伤。RSA 常与子宫内膜基质细胞 （ESC） 蜕膜化缺陷相 关，目前缺乏有效的代谢靶向疗法。 2026 年 1 月 8 日，上海交通大学医学院附属新华医院 赵健元 研究员 、复旦大学附属妇产科医院 金莉萍 教授 、上海交通大学医学院附属国际和平妇幼保健院 李明清 教授等， 在 Cell 子刊 Cell Metabolism 上发 表了题为： Endometrial stromal cell-derived TMAO sustains decidualization to prevent recurrent spontaneous abortion 的研究论文。 该研究首次揭示了蜕膜组织中 氧化三甲胺 （TMAO） 代谢失调导致 反复自然流产 （RSA） 的分子机制， 而补充 TMAO 可挽救部分 反复自然流产 （RSA） 患者 子宫内膜基质细胞 （ESC） 的 蜕膜化缺陷，从而 为部分病因不明的 RSA 患者带来简单、精准的潜 ...

Core Insights - The article discusses the groundbreaking research published in Science, which presents the Chinese Immune Multi-Omics Atlas (CIMA), a comprehensive immune cell atlas based on over 10 million peripheral blood immune cells from 428 individuals in China, providing unprecedented insights into the immune system's functioning [4][30]. Group 1: Research Breakthroughs - CIMA represents the world's first immune cell atlas with a scale of over 10 million cells, integrating genomic, proteomic, RNA, and epigenomic data to create a high-resolution immune multi-omics map [4][8]. - The research identified 73 immune cell subtypes, including rare cells that constitute less than 0.1% of the blood, which play crucial roles in specific immune responses [8][9]. - The study established detailed "identities" for each cell type, documenting their distribution and gene expression characteristics, while exploring associations with physiological factors like age and gender [9][12]. Group 2: Gene Regulation Insights - The research mapped the gene regulatory networks of immune cells, revealing how transcription factors precisely control over 10,000 target genes, with unique regulatory patterns for different immune cell types [12][13]. - It highlighted the dynamic nature of the regulatory systems in immune cells, showing that nearly half of the genetic regulatory effects change with cell state during B cell and monocyte differentiation [13][30]. - The study also focused on non-coding regions, identifying 9,600 genetically regulated genes and over 50,000 chromatin open regions, with one-third of regulatory effects being cell type-specific [13][30]. Group 3: Disease Risk Mapping and AI Integration - The research integrated data from 154 molecular and disease traits, discovering 1,196 significant genetic associations across 68 immune cell types, with 73.2% of these associations being cell type-specific [15][30]. - An example provided is the identification of a key variant that regulates gene expression in regulatory T cells, influencing asthma risk, thus paving the way for precision treatment strategies [15][30]. - The team developed an innovative AI solution, the CIMA Cell Language Model, which predicts chromatin accessibility and assesses the functional impact of non-coding variants, demonstrating high accuracy in 32 immune cell types [18][30]. Group 4: Applications and Future Directions - The CIMA study exemplifies a new paradigm in precision health research, enabling digital analysis and insights into immune health, which can empower disease prevention and health management [22][30]. - A larger-scale CIMA Phase II plan has been initiated, expanding research to autoimmune diseases, cardiovascular diseases, and infectious diseases, utilizing new technologies for comprehensive immune mechanism analysis [25][30]. - The developed "Immune Translation Map" AI assessment model allows for high-precision evaluations of individual immune status, translating cutting-edge research into accessible health products [26][30].

撰文丨王聪 编辑丨王多鱼 排版丨水成文 胆囊癌 （ Gallbladder Cancer，GBC ） 是胆道系统中最常见的恶性肿瘤，可分为常见的腺癌亚型以及罕见的腺鳞癌和神经内分泌癌等亚型。2022 年全球报告 了 122491 例新增病例和 89000 例死亡病例。 胆囊癌的死亡率极高，在目前的临床实践中，只有少数处于早期阶段的患者能够通过手术治愈。对于大多数晚期病例，度伐利尤单抗联合吉西他滨和顺铂是标准 治疗方案，但五年生存率仍低于 10%。在临床试验中，已对几种靶向 ErbB 的治疗药物和免疫检查点阻断疗法进行了研究，但仅在晚期胆囊癌中获得了适度的生 存期延长。 要取得更具临床意义的成果，转化上的突破仍至关重要，因此，深入探究胆囊癌的分子特征对于改进临床治疗不可或缺。 2026 年 1 月 8 日， 复旦大学附属中山医院 樊嘉 院士、 高强 教授 团队联合 中国科学院上海药物研究所 周虎 研究员、中国科学院分子细胞科学卓越创新中心 高大明 研究员、 上海交通大学医学院附属新华医院 龚伟 教授及燃石医学的研究人员 （ 付子乐 、 宋远丽 、 刘分 、 陈律 和 蔡尚立 为论文共同第一作者 ） ， 在 Ca ...

Core Viewpoint - The recent research highlights the role of tertiary lymphoid structures (TLS) in enhancing anti-tumor immunity and their prognostic value in cancer immunotherapy, emphasizing the need to understand the mechanisms driving TLS formation and to develop strategies to induce TLS for effective anti-tumor therapies [2][6]. Group 1: Research Findings - A study published in *Cancer Cell* reveals that IGLL5 B cell subpopulation disrupts TLS formation and suppresses anti-tumor immunity, particularly in bladder cancer, providing a potential new target for immunotherapy [3][10]. - The research identified an IGLL5+ B cell subpopulation in bladder cancer through single-cell RNA sequencing and spatial transcriptomics [7]. - In engineered humanized mouse models, IGLL5+ B cells compromised the integrity of TLS and weakened the response to immunotherapy [8]. Group 2: Mechanisms and Implications - The mechanism involves IGLL5+ B cells interacting with high endothelial venules (HEV) via IGLL5-LTβR, leading to conformational changes in LTβR that inhibit the non-canonical NF-κB signaling pathway, ultimately resulting in TLS disintegration [8]. - Preclinical studies indicate that blocking IGLL5 can maintain TLS and enhance the efficacy of immunotherapy in patient-derived xenograft models and pan-cancer models [9]. - Targeting IGLL5+ B cells presents a new strategy for enhancing TLS-dependent cancer immunotherapy [10].

撰文丨王聪 编辑丨王多鱼 排版丨水成文 尽管药物研发领域取得了诸多进展，但仍有约 90% 的可成药疾病靶点缺乏小分子药物。随着诸如 AlphaFold 等蛋白质结构预测技术的进步， 全基因组药物发现 已成为一个更可实现的目标。然而，目前使 用的 虚拟筛选 （ Virtual Screening ） 工具远不能满足这一需求。现有的方法 （无论是经典的分子对接还 是深度学习方法） ，仍存在着计算成本都太高、无法覆盖全基因组靶点等问题。 因此，研究人员希望能够开发出 一种有效的 全基因组虚拟筛选 方法，以快速识别人类基因组中每个可成 药靶点的小分子配体。 如今，这一局面正被打破。来自 清华大学 的研究团队推出了 AI 驱动的超高通量药物虚拟筛选平台—— DrugCLIP ， 首次实现 全基因组规模的虚拟筛选 ，将传统方法需数年的计算任务压缩至 24 小时内，效率 提升最高达 1000 万倍。 该研究于 2026 年 1 月 8 日，清华大学智能产业研究院 （ AIR ） 兰艳艳 教授 联合清华大学生命科学学 院学院 张伟 副教授、 闫创业 副教授及化学系 刘磊 教授 （ 贾寅君 、 高博文 、 谭佳 鑫 、 郑济青 ...

编辑丨王多鱼 排版丨水成文 热带森林 储存了全球约一半的 地上生物量碳 （AGC） ，但广大区域正遭受干扰影响，包括农业扩张导致 的毁林以及火灾、选择性采伐和边缘效应引发的退化。随着时间的推移，受干扰森林能够恢复，逐步重建 碳储量和生态功能。然而，关于恢复速率如何随干扰规模、类型和地理位置变化的问题仍缺乏量化研究。 2026 年 1 月 7 日，清华大学 李伟 副教授 、 法国气候与环境科学实验室 Philippe Ciais 教授教授 作为通 讯作者 （ 徐伊迪 为论文第一作者 ） ，在国际顶尖学术期刊 Nature 上发表了题为： Small persistent humid forest clearings drive tropical forest biomass losses 的研究论文。 该研究基于高分辨率的森林扰动和生物量数据，构建了格点尺度的森林扰动植被恢复数据库，并在此基础 上开发了一个集成高分辨率遥感数据和森林扰动恢复数据库的森林碳簿记模型。利用该模型估算了 1990- 2020 年间森林扰动导致的植被碳储量时空变化动态，明确了不同干扰类型和扰动斑块大小对森林植被碳储 量及碳密度变化的具体 ...