Nature Biomedical Engineering最新文献_第5页

Defining attributes of effective binders for AI-assisted CAR design. 定义人工智能辅助CAR设计的有效粘合剂的属性。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-09-09 DOI: 10.1038/s41551-026-01792-7

引用次数: 0

Author Correction: A base editor for the long-term restoration of auditory function in mice with recessive profound deafness. 作者更正：隐性深度耳聋小鼠听觉功能长期恢复的碱基编辑器。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-09-07 DOI: 10.1038/s41551-026-01794-5

Chong Cui, Shengyi Wang, Daqi Wang, Jingjing Zhao, Bowei Huang, Biyun Zhu, Yuxin Chen, Honghai Tang, Yu Han, Cheng Ye, Dan Mu, Chengdong Zhang, Yuan Yang, Yihan Bao, Jun Lv, Shuang Han, Geng-Lin Li, Huawei Li, Yilai Shu

引用次数: 0

Engineering inflammation-responsive proteins through nitric oxide-caged amino acids. 通过一氧化氮笼氨基酸工程炎症反应蛋白。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-31 DOI: 10.1038/s41551-026-01782-9

Wenkang Cai, Junhao Cui, Zhiying Zeng, Zexian Xiang, Yuanzhe Xie, Yeyu Su, Yi Zuo, Yingze Liu, Haoyu Wang, Liying Chang, Xue Wang, Jingjing Wang, Jun-An Ma, Tao Liu

{"title":"Engineering inflammation-responsive proteins through nitric oxide-caged amino acids.","authors":"Wenkang Cai, Junhao Cui, Zhiying Zeng, Zexian Xiang, Yuanzhe Xie, Yeyu Su, Yi Zuo, Yingze Liu, Haoyu Wang, Liying Chang, Xue Wang, Jingjing Wang, Jun-An Ma, Tao Liu","doi":"10.1038/s41551-026-01782-9","DOIUrl":"https://doi.org/10.1038/s41551-026-01782-9","url":null,"abstract":"Nitric oxide is upregulated in inflammatory tissues but has not been used to directly control the activity of folded proteins. Here we report a protein engineering strategy that enables selective restoration of protein function in nitric oxide-rich environments. Protein activity is temporarily suppressed by site-specific substitution of a catalytically or structurally essential glutamate residue with a synthetic amino acid whose side chain is chemically masked. Exposure to nitric oxide triggers decaging of this residue, regenerating the native glutamate and restoring protein function. Using this approach, we engineer nitric oxide-responsive variants of antibodies, enzymes, cytokines, bacterial toxins and viral capsids. In mouse models, this strategy enables inflammation-localized protein activation, selective viral gene delivery in inflamed tissues and rapid detection of intestinal inflammation using engineered probiotic biosensors. These results establish nitric oxide-triggered chemical reactivation of proteins as a generalizable method for post-translational control of protein function, with potential applications in inflammation-targeted therapeutics, gene delivery and biosensing.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.3,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developmental deviations of association-network structural connectivity in youths with ADHD predict symptom and treatment outcomes. 青少年ADHD患者关联-网络结构连通性的发展偏差预测症状和治疗结果。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-31 DOI: 10.1038/s41551-026-01779-4

Xiaoyu Xu, Zhao Fu, Haoshu Xu, Kangfuxi Zhang, Jing Cong, Hang Yang, Yang Li, Yilu Zhao, Xiangyu Zheng, Arielle S Keller, Ting Xu, Runsen Chen, Weidong Cai, Qingjiu Cao, Li Yang, Zaixu Cui

{"title":"Developmental deviations of association-network structural connectivity in youths with ADHD predict symptom and treatment outcomes.","authors":"Xiaoyu Xu, Zhao Fu, Haoshu Xu, Kangfuxi Zhang, Jing Cong, Hang Yang, Yang Li, Yilu Zhao, Xiangyu Zheng, Arielle S Keller, Ting Xu, Runsen Chen, Weidong Cai, Qingjiu Cao, Li Yang, Zaixu Cui","doi":"10.1038/s41551-026-01779-4","DOIUrl":"10.1038/s41551-026-01779-4","url":null,"abstract":"Attention deficit hyperactivity disorder (ADHD) lacks validated biomarkers for tracking symptom trajectories or guiding treatment selection in youth. Here we quantify individual deviations from normative age-related trajectories of white-matter structural connectivity across two independent datasets: 6,687 typically developing and 1,114 ADHD scans from a longitudinal developmental cohort, and 355 typically developing and 477 ADHD participants from an independent cohort. Youths with ADHD showed pronounced structural connectivity deviations enriched towards the association end of the sensorimotor-association connectional axis. A subset of higher-order association connections showed ADHD-specific developmental reductions in deviations beyond typical developmental patterns, and these changes mediated age-related declines in ADHD symptoms. Within-individual decreases in deviation over 2 years tracked symptom improvement. Baseline deviations predicted 12-week treatment response to atomoxetine but not methylphenidate, and follow-up imaging revealed treatment-related reductions in deviation. Together, these findings identify structural connectivity deviation as a developmental biomarker with prognostic relevance for ADHD, supporting precision care through symptom monitoring and treatment stratification.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.3,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-centric feedback loops for next-generation immunotherapy development. 下一代免疫疗法发展的数据中心反馈回路。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-28 DOI: 10.1038/s41551-026-01785-6

Rotem Shalita, Ido Amit

{"title":"Data-centric feedback loops for next-generation immunotherapy development.","authors":"Rotem Shalita, Ido Amit","doi":"10.1038/s41551-026-01785-6","DOIUrl":"https://doi.org/10.1038/s41551-026-01785-6","url":null,"abstract":"Despite explosive growth in biomedical data generation, driven largely by genomics, and in computational capabilities, the probability that a candidate entering phase I ultimately reaches approval has remained stubbornly low over the past decades. This paradox points to a central bottleneck not in data generation, but in converting biological and clinical data into decisions that govern progression, redesign or termination. Here we argue that drug development should be reframed from a linear pipeline into an iterative learning system driven by continuous data feedback. We outline a data-centric framework in which high-dimensional, multimodal molecular and perturbation data, particularly single-cell and spatial readouts, are used to iteratively refine disease models, therapeutic hypotheses, molecular designs and patient stratification strategies across discovery and clinical stages. Using immunotherapies as a proof-of-concept domain, we propose that single-cell molecular readouts from therapeutic perturbations can both de-risk development and deepen mechanistic understanding of immune responses in humans. Finally, we draw parallels to reinforcement learning, in which human molecular and clinical data provide the feedback signal that updates mechanistic models and guides the design of subsequent interventions. Embracing this paradigm offers a path towards more mechanistically grounded, context-aware therapies with higher translational success.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.3,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148851089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Engineered autophagy receptors administered with extracellular vesicles eliminate pathological Tau and TDP-43. 与细胞外囊泡一起使用的工程化自噬受体可消除病理性Tau和TDP-43。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-26 DOI: 10.1038/s41551-026-01774-9

Huishan Guo, Alexandre Savard, Charlotte Manser, Kallol Dutta, James A Taylor, Maxime W C Rousseaux, Silvia Pozzi, Jean-Pierre Julien, Stephen Baird, Derrick Gibbings

{"title":"Engineered autophagy receptors administered with extracellular vesicles eliminate pathological Tau and TDP-43.","authors":"Huishan Guo, Alexandre Savard, Charlotte Manser, Kallol Dutta, James A Taylor, Maxime W C Rousseaux, Silvia Pozzi, Jean-Pierre Julien, Stephen Baird, Derrick Gibbings","doi":"10.1038/s41551-026-01774-9","DOIUrl":"https://doi.org/10.1038/s41551-026-01774-9","url":null,"abstract":"In neurodegenerative diseases such as frontotemporal dementia and amyotrophic lateral sclerosis, pathological forms of proteins such as Tau and TDP-43 accumulate within large heterogeneous inclusions inside cells. Current strategies to eliminate such aberrant protein species in patients encounter three main challenges: crossing the blood-brain barrier and plasma membrane, specifically recognizing pathological forms of proteins, and engaging mechanisms to eliminate large entities. Here we fuse LC3A, a central protein in the recruitment of substrates into autophagosomes, to cytoplasm-stable antibodies. These engineered autophagy receptors, targeting Tau or TDP-43, are delivered using small extracellular vesicles and reduce pathology in models, including Tau P301S adult primary mouse neurons, TDP-43G298S iPSC-derived motor neurons and after intravenous injection in Tau P301S mice. Similarly, adeno-associated-virus-mediated delivery in TDP-43ΔNLS mice enhances clearance of pathological TDP-43. This targeted degradation strategy allows delivery into the brain while capitalizing on the specificity of antibodies and the ability of autophagy to degrade large intracellular entities.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.3,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148830930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generalizable multiple-instance learning for computational pathology. 计算病理学的可推广多实例学习。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-26 DOI: 10.1038/s41551-026-01766-9

引用次数: 0

A regulatory sandbox for consumer health sensors in clinics 诊所消费者健康传感器的监管沙盒。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-25 DOI: 10.1038/s41551-026-01781-w

Jascha Drew Jäger, Dietmar Schaffarczyk, Kerstin Noelle Vokinger, Noé Brasier, Jörg Goldhahn

引用次数: 0

Targeting tumour-neuron synapses with intracavitary RNA delivery prevents glioblastoma recurrence. 靶向肿瘤神经元突触与腔内RNA递送预防胶质母细胞瘤复发。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-25 DOI: 10.1038/s41551-026-01757-w

Zhi Li, Zhao-Zhe Hao, Yihe Zhang, Nana Xu, Tiebao Meng, Haokun Jiao, Cong Wang, Furong Chen, Yuan Xie, Changyu Wang, Meiqin Tang, Hao Duan, Jing Wang, Haoqiang He, Nannan Bai, Chuanmiao Xie, Ruiwang Huang, Zhenqiang He, Sheng Liu, Huilong Guo, Yonggao Mou

{"title":"Targeting tumour-neuron synapses with intracavitary RNA delivery prevents glioblastoma recurrence.","authors":"Zhi Li, Zhao-Zhe Hao, Yihe Zhang, Nana Xu, Tiebao Meng, Haokun Jiao, Cong Wang, Furong Chen, Yuan Xie, Changyu Wang, Meiqin Tang, Hao Duan, Jing Wang, Haoqiang He, Nannan Bai, Chuanmiao Xie, Ruiwang Huang, Zhenqiang He, Sheng Liu, Huilong Guo, Yonggao Mou","doi":"10.1038/s41551-026-01757-w","DOIUrl":"10.1038/s41551-026-01757-w","url":null,"abstract":"Tumour-neuron interactions and malignant synapse formation drive glioblastoma progression, recurrence and neurological dysfunction, but systemic inhibition of synaptic signalling causes unacceptable neurotoxicity. Here we defined the spatial and molecular determinants of malignant synapses by analysing intact human glioblastoma specimens, revealing enrichment of synapse-like structures and synapse-associated gene programmes at the tumour-brain interface. Spatial and transcriptomic analyses highlighted the neurotrophic receptor TrkB as a candidate therapeutic target at the tumour-brain interface. Guided by this target, we developed an intracavitary, multiresponsive hydrogel that locally delivers small interfering RNA to silence TrkB in residual tumour cells after surgery. In syngeneic and patient-derived glioblastoma models, treatment suppressed tumour regrowth and prolonged survival; in the syngeneic GL261 model, median survival increased from 32 to 67 days, with more than 30% of treated animals surviving beyond 90 days. TrkB silencing reduced excitatory synaptic input to tumour cells and alleviated tumour-associated anxiety and memory deficits without impairing motor function. Combination with radiotherapy further reduced invasive growth at the tumour-brain interface and extended survival. Together, these findings establish a spatially restricted, mechanism-guided therapeutic strategy for glioblastoma.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.3,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148819008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

nnMIL: a generalizable multiple instance learning framework for computational pathology. nnMIL：用于计算病理学的可推广的多实例学习框架。

IF 26.3 1区医学

Nature Biomedical Engineering Pub Date : 2026-08-25 DOI: 10.1038/s41551-026-01767-8

Xiangde Luo, Jinxi Xiang, Yuanfeng Ji, Ruijiang Li

{"title":"nnMIL: a generalizable multiple instance learning framework for computational pathology.","authors":"Xiangde Luo, Jinxi Xiang, Yuanfeng Ji, Ruijiang Li","doi":"10.1038/s41551-026-01767-8","DOIUrl":"https://doi.org/10.1038/s41551-026-01767-8","url":null,"abstract":"Computational pathology holds substantial promise for improving diagnosis and guiding treatment decisions. Recent pathology foundation models enable the extraction of rich patch-level representations from large-scale whole-slide images (WSIs), but current approaches for aggregating these features into slide-level predictions remain constrained by design limitations that hinder generalizability and reliability. Here we present nnMIL, a simple yet broadly applicable multiple-instance learning framework that connects patch-level foundation models to robust slide-level clinical prediction. nnMIL introduces random sampling at both the patch and feature levels, enabling large-batch optimization, task-aware sampling strategies, and efficient and scalable training across datasets and model architectures. A lightweight aggregator performs sliding-window inference to generate ensemble slide-level predictions and supports principled uncertainty estimation. Across 40,000 WSIs encompassing 35 clinical tasks and 4 pathology foundation models, nnMIL consistently outperformed existing MIL methods for disease diagnosis, histologic subtyping, molecular biomarker detection and pan-cancer prognosis prediction. It further demonstrated strong cross-model generalization, reliable uncertainty quantification and robust survival stratification in multiple external cohorts. In conclusion, nnMIL offers a practical and generalizable solution for translating pathology foundation models into clinically meaningful predictions, advancing the development and deployment of reliable AI systems in real-world settings.","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":26.3,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148818933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0