这项最新研究表明，在远古地球极端低黏度环境下，基于正确核心几何形态的发电机作用展现出与流体黏度无关的特性，证明流体黏度在模拟中的作用可忽略不 计。采用早期地球几何结构的模型产生的磁场强度和形态，不仅与远古古地磁数据相符，且与现今地球磁场表现出显著相似性。 编辑丨王多鱼 排版丨水成文 地球磁场 的产生可能已持续存在至少 35 亿年，最初由地核的长期冷却维持，而近期则由固体内核的生长驱动。 目前的 地球发电机 数值模型已成功模拟出类地磁场并接近真实动态机制。然而，热演化模型和古地磁记录表明，在大部分地球磁场历史时期，地球发电机的运行 并不依赖固体内核的存在。对于全液态地核的发电机机制，科学界仍缺乏深入理解。 2025 年 7 月 30 日，南方科技大学 林玉峰 副教授作为第一作者兼共同通讯作者，在国际顶尖学术期刊 Nature 上发表了题为 ： Invariance of dynamo action in an early-Earth model 的研究论文。 该研究揭示了早期地球模型中发电机作用的不变性，从而对固体内核在产生地球磁场时空变化中的核心作用提出了根本性质疑。 这些发现这引发了关于地球固体内核在产生地 ...

撰文丨王聪 编辑丨王多鱼 排版丨水成文 最近几年， 异种移植 的基础与临床研究取得里程碑式突破。 2021 年 10 月，纽约大学朗格尼医学中心首次将基因编辑的 猪肾脏 移植给了一位脑死亡女性。 2022 年 1 月，马里兰大学医学院进行了世界首例活人移植基因编辑 猪心脏 的手术，患者在移植后存活了约 2 个月时间。 2025 年 3 月， 空军军医大学西京医院 窦科峰 院士、 王琳 教授、 董海龙 教授、 陶开山 教授 及中科奥格生物科技有限公司 潘登科 教授等在国际顶尖学术期 刊 Nature 上发表论文 【1】 。介绍了世界首例将基因编辑改造的 猪肝脏 移植到脑死亡的人类受体的案例 （移植手术于 2024 年 3 月 进行） ，结果显示，基因 编辑改造的猪肝脏能够在人体内存活并发挥功能，有望成为等待人类供体的肝衰竭患者的过渡疗法。 基因工程猪的最新进展推动了猪到人类的异种器官移植研究，尤其是 心脏 、 肾脏 和 肝脏 的 异种移植 研究。 在这项最新研究中，研究团队对一名接受猪肝脏异种移植的人类患者在去世时其外周血和移植肝脏中的免疫细胞群进行了表征，该患者在 异种移植 后接受了为期 10 天的监测，监测 ...

Core Viewpoint - The article emphasizes the significant role of metabolic regulation in mammalian embryogenesis, challenging the traditional view that metabolism merely supports developmental processes passively [2][4]. Group 1: Metabolic Regulation in Early Development - Metabolic needs during early embryonic development are critical, with pyruvate being essential for maintaining redox balance [4]. - The metabolic remodeling drives zygotic genome activation (ZGA), where mitochondrial TCA cycle enzymes temporarily localize to the nucleus in a pyruvate-dependent manner, closely linked to epigenetic reprogramming [4]. - Lactate accumulation in early embryos is crucial, and inhibiting lactate production or uptake can halt development at the two-cell stage [4]. Group 2: Metabolic Changes During Blastocyst Formation - As embryos progress from the two-cell stage to the blastocyst stage, significant metabolic activity changes occur, including increased mitochondrial activity and enhanced pyruvate oxidation [4]. - The dynamic changes in lipids during this stage are vital for establishing polarity in the outer cells of the morula [4]. Group 3: Metabolic Activity During Implantation - Lipids and their derivatives are essential for blastocyst implantation, with fatty acid-related inflammatory responses aiding in establishing the maternal-fetal interface and optimizing uterine receptivity [4]. Group 4: Metabolic Features in Gastrulation and Organogenesis - Metabolic gradients, such as spatially and temporally specific glucose metabolism waves, play a regulatory role in gastrulation [4]. Group 5: Metabolic Characteristics of Embryo Dormancy - Increased autophagic activity generates more nutrients, and higher levels of taurine and hypotaurine provide antioxidant protection during embryo dormancy [4]. Group 6: Advanced Methods for Assessing Embryonic Metabolism - The article discusses advanced methods for evaluating embryonic metabolism, including metabolomics for small embryos, spatial metabolomics, and Raman spectroscopy for assessing embryo quality in vitro [4].

Core Viewpoint - The emergence of DeepSeek-R1, an open-source large language model (LLM) developed by a Chinese startup, has revolutionized the deployment of AI in hospitals, significantly enhancing efficiency and reducing costs compared to existing models like ChatGPT [2][12]. Group 1: Deployment and Impact - DeepSeek-R1 was released in January 2025 and quickly became the most downloaded chatbot in the US Apple App Store, surpassing OpenAI's ChatGPT [2]. - As of May 8, 2025, DeepSeek-R1 has been deployed in over 755 hospitals across China, including top-tier hospitals and grassroots medical institutions, with more than 500 achieving local deployment [5][8]. - The model is capable of various tasks, including clinical services, hospital operations, and personal health management, providing significant support in diagnosis, treatment recommendations, and administrative tasks [13][21]. Group 2: Advantages of DeepSeek-R1 - The model's deployment cost is significantly lower than traditional AI systems, with a complete local deployment costing under $100,000, making it accessible for many smaller hospitals [21]. - DeepSeek-R1's advanced reasoning capabilities are comparable to top international models, essential for handling complex medical tasks [22]. - The open-source nature allows hospitals to customize and integrate the model into existing systems, enhancing its utility [22]. Group 3: Regulatory Challenges - The rapid deployment of DeepSeek-R1 has highlighted a regulatory "gray area," raising concerns about patient safety and the need for a robust regulatory framework [6][10]. - The lack of clear classification standards for AI applications in healthcare leads to ambiguity regarding which applications are considered high-risk [32]. - The current regulatory environment does not adequately address the unique challenges posed by large language models, necessitating immediate reforms [35]. Group 4: Recommendations for Regulation - The article calls for a risk-based classification system for AI applications in healthcare, distinguishing between high-risk and low-risk applications [35]. - High-risk applications should be regulated as medical devices, requiring stringent approval and monitoring processes [35]. - Continuous monitoring and evaluation of AI applications in real-world settings are essential to ensure safety and effectiveness [38].

Core Viewpoint - The article emphasizes the importance of selecting high-quality journals in the biomedical field for researchers, highlighting the need to avoid low-quality publications and focus on reputable ones to enhance research visibility and impact [1]. Group 1: Journal Highlights - The American Journal of Bioethics is a leading international journal in bioethics, focusing on ethical challenges in health sciences, with a 2024 impact factor of 20.8 and ranked 1st in multiple categories [3][4][5]. - The journal "Amyloid" is the official journal of the International Society of Amyloidosis, publishing research on amyloid proteins and related diseases, with a 2024 impact factor of 7.4 and high rankings in biochemistry and medicine [9][10][12]. - The Journal of Oral Microbiology explores oral microbiology and related health issues, with a 2024 impact factor of 5.5 and a strong ranking in microbiology [14][17]. - The journal "Artificial Cells, Nanomedicine, and Biotechnology" publishes interdisciplinary research on artificial cells and nanomedicine, with a 2024 impact factor of 4.5 and notable rankings in materials science and biotechnology [19][22][23].

Core Viewpoint - Cancer-associated fibroblasts (CAF) play a critical role in supporting tumor growth and metastasis through extracellular matrix remodeling, paracrine signaling, and immune suppression, which limits the efficacy of immune checkpoint blockade (ICB) therapies [2][3]. Group 1 - The study published by researchers from the University of Chicago in the journal Nature reveals that NNMT promotes the recruitment of myeloid-derived suppressor cells (MDSC) into tumors via CAF, leading to the formation of an immunosuppressive tumor microenvironment (TME) [4]. - The research demonstrates that NNMT is expressed in all CAF subtypes and induces H3K27me3 hypomethylation, which facilitates the secretion of complement proteins that recruit MDSC into the tumor [7]. - The team developed a potent and specific NNMT inhibitor (NNMTi) that reduced tumor burden and metastasis in various mouse tumor models by decreasing CAF-mediated MDSC recruitment and reactivating CD8+ T cell activation, thereby restoring the efficacy of ICB therapy [9]. Group 2 - Overall, the study indicates that NNMT is a key regulatory factor of immunosuppression in the tumor microenvironment and represents a promising new target for alleviating immune suppression and enhancing cancer immunotherapy effectiveness [11].

Core Viewpoint - The article discusses the development of an AI-driven virtual laboratory that enables multidisciplinary research teams to tackle complex scientific problems, specifically in the context of designing new nanobodies for SARS-CoV-2 [2][4][11]. Group 1: AI-Driven Virtual Laboratory - Researchers from Stanford University and the Chan Zuckerberg Biohub have created a virtual laboratory platform powered by AI agents, which can autonomously design and execute complex research strategies [2][4]. - The virtual lab allows human scientists to pose scientific questions while AI agents, including a "Chief Scientist Agent" and various "Specialist Agents," collaborate to advance research [5][6]. Group 2: Research Outcomes - Within days, the virtual laboratory successfully designed 92 novel nanobodies, with two showing the ability to bind to the spike protein of new SARS-CoV-2 variants during laboratory validation [9][11]. - The research demonstrates that AI agents can generate creative and rational solutions to scientific challenges, enhancing human scientists' capabilities rather than replacing them [11]. Group 3: Implications and Future Applications - This study marks the first instance of autonomous AI agents effectively solving a challenging scientific research problem from start to finish, showcasing a new paradigm where AI drives the entire research process [11]. - The virtual laboratory platform is designed for biomedical research but can be adapted for broader scientific fields, indicating its potential for widespread application [11].

Core Viewpoint - The article discusses the limitations of current cancer therapies based on secreted proteins and highlights a new research study that identifies potential immunotherapy targets through a cancer immunology data platform [2][3][12]. Group 1: Research Findings - The study developed a cancer immunology data platform called CIDE, which integrates 90 multi-omics datasets covering 8,575 tumor samples across 17 types of solid tumors [8][12]. - CIDE systematically identifies genes related to immunotherapy outcomes and has revealed secreted proteins such as AOAH, CR1L, COLQ, and ADAMTS7 as new immune checkpoint blockade (ICB) regulators [9][15]. - AOAH enhances immunotherapy through dual mechanisms: increasing T cell receptor (TCR) sensitivity to weak antigens and removing inhibitory lipids that suppress dendritic cell function [10][15]. Group 2: Implications for Cancer Treatment - The findings suggest that the identified secreted proteins could serve as precise targets for a new generation of immunotherapies, overcoming the limitations of traditional therapies like IL-2 and VEGF inhibitors, which have low response rates and unstable efficacy [17]. - AOAH's validation across multiple tumor models indicates its potential as a broad-spectrum immune enhancer [18]. Group 3: Future Directions - The research aims to expand the functional map of secreted proteins, particularly focusing on the 61% of previously unreported proteins related to cancer, to discover new molecules that regulate the immune microenvironment [20]. - There is a focus on targeting lipid-immune interactions based on AOAH-related lipid metabolism pathways for developing small molecule drugs or combination therapies [20]. - The study emphasizes the need for clinical translation of molecules like AOAH as biomarkers or therapeutic targets through preclinical and clinical trials [20].

Core Viewpoint - Latent Labs has developed a groundbreaking generative AI model, Latent-X, which enables the design of functional protein binders with atomic-level precision, significantly improving the drug discovery process [6][7][26]. Group 1: Company Background - Simon Kohl, a former researcher at DeepMind, founded Latent Labs after leaving the company in late 2022, focusing on advanced protein design models to aid biopharmaceutical companies [2]. - Latent Labs secured $50 million in funding in February 2025 to further its mission in drug development [2]. Group 2: Technology and Innovation - Latent-X can design functional protein binders, including macrocyclic peptides and small protein binders, with unprecedented efficiency and accuracy [6][7]. - The model generates reliable protein binders by solving geometric challenges at the atomic level, producing high-affinity and specificity binders [7][20]. - Latent-X demonstrated a significant improvement in efficiency, requiring only 30-100 candidates per target to achieve results that typically need millions of candidates [7][18]. Group 3: Performance Validation - The research team tested Latent-X on seven benchmark target proteins related to viral infections, tumor regulation, and neurodegeneration [11][12]. - Latent-X achieved a hit rate of 91%-100% for macrocyclic peptides and 10%-64% for small protein binders across the target proteins [18]. - The best-designed macrocyclic peptides reached micromolar affinity, while small protein binders achieved picomolar affinity, surpassing other design models [19]. Group 4: Features and Usability - Latent-X allows users to generate both protein sequences and structures simultaneously, outperforming previous methods that generated them sequentially [23]. - The platform is user-friendly, requiring no coding skills, and provides a complete workflow for laboratory validation [21][29]. - Latent-X is scalable and has successfully generated various therapeutic binders, with plans for further expansion [22]. Group 5: Competitive Advantage - Latent-X excels in generating binders for previously unseen targets, achieving higher simulation hit rates with fewer samples compared to other models [24][28]. - The model adheres to atomic-level biochemical rules, creating structures that are chemically viable and suitable for drug development [28].

Core Viewpoint - The article discusses the increasing global plastic consumption and its environmental impact, particularly focusing on microplastics and nanoplastics, which pose potential biological risks to human health [2][3][6]. Group 1: Plastic Consumption and Environmental Impact - In 2022, global plastic production was approximately 390 million tons, with only about 9% being recycled, leading to significant accumulation of microplastics and nanoplastics (MNP) [3]. - An individual may be exposed to between 74,000 and 121,000 MNP particles annually, with these particles detected in various human tissues, including kidneys, liver, lungs, and spleen [3]. Group 2: Research Findings on Reproductive Health - A study published by researchers from Zhejiang University found polyethylene (PE) and polyvinyl chloride (PVC) nanoplastics in human follicular fluid and seminal plasma, which are associated with decreased fertilization success rates and reduced sperm quality [4][5]. - The study utilized liquid phase extraction combined with pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) to analyze samples from 51 couples undergoing in vitro fertilization (IVF) [7]. - Average concentrations of PE and PVC in follicular fluid were 1.21 µg/g and 1.85 µg/g, respectively, while in seminal plasma, they were 3.02 µg/g and 2.67 µg/g [8]. - Higher concentrations of PE and PVC in follicular fluid were linked to significantly lower fertilization success rates, while PVC concentration in seminal plasma was associated with reduced sperm motility [10].