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An enzyme-gated bioorthogonal catalytic nanoreactor for tumor specific prodrug activation

Nano Research 2025年第2期18卷 557-570页

作者： Yuheng Guo Fang Jiang Xiaohui Zhu Wen He Sijie Song Xuecen Shou Mengnan Wu Ting Wu Tingjing Huang Zhi Ye Xuyang Wang Zhitong Chen Yu He Yuhang Yao Zhaowei Chen Huanghao Yang New Cornerstone Science Laboratory MOE Key Laboratory for Analytical Science of Food Safety and BiologyCollege of ChemistryFuzhou UniversityFuzhou 350108China Food Inspection and Quarantine Technical Center of Shenzhen Customs District of the People's Republic of China Shenzhen 518045China Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Department of Chemistry University College LondonLondon WC1H 0AJUK

Bioorthogonal catalysis mediated by abiotic transition metal catalysts(TMCs)is emerging as a momentum-gathering strategy for in situ generation of ***,the unpredictable leakage and deposition of TMCs in living systems easily lead to nonspecific exposure of catalysts and concomitant off-target prodrug ***,we propose an enzyme-gated bioorthogonal catalytic nanoreactor constructed from hyaluronic acid(HA)-coated dendritic mesoporous silica nanoparticles(DMSNs),where the latter serves as a host for robustly immobilizing organometallic Ru(ll)catalysts via covalent *** covalent immobilization of catalysts within the nanoscaffold effectively avoids nonspecific metal leakage under biological ***,the grafted HA not only acts as a"gatekeeper"preventing unintended catalyst exposure in nontargeted tissues but also acts as a ligand targeting CD44 overexpressed cancer *** receptor-mediated endocytosis into tumor cells,HA is degraded by the overexpressed hyaluronidase-1,leading to the channel opening of the nanoreactors and hence gaining the accessibility of Ru(ll)complexes to *** therapeutic potency of this enzyme-gated nanoreactor in mediating site-specific activation of caged prodrugs was systematically demonstrated both in cellular settings and in tumor-bearing murine *** enzyme-gated strategy enhances the efficacy of localized treatment while avoiding off-target prodrug activation,paving the way for advancing bioorthogonal catalysis for disease management in a safe and effective way.

关键词： bioorthogonal catalysis prodrugs enzyme-gated catalyst immobilization cancer therapy

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Axis-Guided Quality Assessment and Multi-label Hippocampal and Ventricular Segmentation in Low-Resolution Pediatric Brain MRI 1st

Axis-Guided Quality Assessment and Multi-label Hippocampal a...

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1st MICCAI Challenge on Low Field Pediatric Brain Magnetic Resonance Image Segmentation and Quality Assurance, LISA 2024, held in Conjunction with Medical Image Computing and Computer Assisted Intervention Conference, MICCAI 2024

作者： Kim, Hyunwook Seo, Jinew Ryu, Seiyoung Park, Joon hyung On, Sungchul Choi, Jinwha Department of Convergence Medicine Asan Medical Institute of Convergence Science and Technology University of Ulsan College of Medicine Asan Medical Center 388-1 Pungnap2-Dong Songpa-Gu Seoul Korea Republic of Department of Biomedical Engineering BK21 Project Asan Medical Center University of Ulsan College of Medicine Seoul Korea Republic of

ISBN: (纸本)9783031830105

The Swoop system of Hyperfine Inc. is an affordable, ultra-low-field MRI developed for use in a clinical setting. However, despite its advantages, the relatively low resolution of 64mT MRI data poses additional challenges, especially in examining small structures such as the hippocampus or vessels. As a part of our attempt at the Low field pediatric brain magnetic resonance Image Segmentation and Quality Assurance (LISA) Challenge 2024, we developed two deep learning-based models. First, to evaluate the image quality of 64mT T2 brain MRI data, we implemented an axis classifier module to improve the model performance. Second, for segmentation of the hippocampus in the MRI, a multi-label learning method was used for more accurate segmentation. With these models, we expect to alleviate the accessibility barrier to brain MRI. © The Author(s) 2025.

关键词： Pediatrics

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Artificial intelligence is transforming the study of proteins:Structures and beyond

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hLife 2025年第4期3卷 162-163页

作者： Haiyan Liu Quan Chen Yufeng Liu MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Biomedical Sciences and Health Laboratory of Anhui Province Anhui Basic Discipline Research Center of Artificial Intelligence Biotechnology and Synthetic BiologyUniversity of Science and Technology of ChinaAnhuiChina School of Biomedical Engineering Suzhou Institute for Advanced ResearchUniversity of Science and Technology of ChinaJiangsuChina Department of Rheumatology and Immunology The First Affiliated Hospital of USTCDivision of Life Sciences and MedicineHefei National Research Center for Physical Sciences at the MicroscaleCenter for Advanced Interdisciplinary Science and Biomedicine of IHMUniversity of Science and Technology of ChinaAnhuiChina

Recently,the Royal Swedish Academy of Sciences announced that one-half of the 2024 Nobel Prize in Chemistry was awarded to David Baker for computational protein design,and the other half was awarded jointly to Demis Hassabis and John Jumper for protein structure *** are the molecule tools of *** carry out their functions,many proteins need to fold into particular three-dimensional(3D)structures,which are programmed by the amino acid sequences of the proteins[1].The goal of protein structure prediction is to predict the 3D structures from given amino acid ***,protein design aims to identify amino acid sequences that achieve desired structural or functional goals.

关键词： amino acid sequences proteindesign computationalproteindesign aminoacids computational protein designand artificialintelligence proteinstructureprediction protein structure predictionproteins

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Three-dimensional quantitative phase imaging evaluating glioblastoma targeting CAR T-cell efficacy 11

Three-dimensional quantitative phase imaging evaluating glio...

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Quantitative Phase Imaging XI 2025

作者： Serafini, Caroline E. Davarzani, Amin Cappabianca, Dan Collazos, Daniela Baez Li, Zhenmin Mamaghani, Deniz Tommasi, Anna Sarko, Lauren La Vonne Denne, Nina Mao, Leidong Saha, Krishanu Karumbaiah, Lohitash Robles, Francisco E. George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology AtlantaGA United States Wallace H. Coulter Dept. of Biomedical Engineering Georgia Institute of Technology Emory University AtlantaGA United States School of Electrical and Computer Engineering College of Engineering University of Georgia AthensGA United States Regenerative Bioscience Center University of Georgia AthensGA United States Department of Biomedical Engineering University of Wisconsin-Madison MadisonWI United States Wisconsin Institute for Discovery University of Wisconsin-Madison MadisonWI United States School of Electrical and Computer Engineering Georgia Institute of Technology 266 Ferst Drive AtlantaGA United States Department of Cellular Biology University of Georgia AthensGA United States Division of Neuroscience Biomedical and Translational Sciences Institute University of Georgia AthensGA United States Edgar L. Rhodes Center for Animal and Dairy Science College of Agriculture and Environmental Science University of Georgia AthensGA United States

ISBN: (纸本)9781510684065

Glioblastoma (GBM) is a highly aggressive brain tumor with limited treatment options and poor patient outcomes. While patient-derived spheroids offer a platform for studying GBM treatment, existing imaging modalities are often destructive or limited to endpoint analyses. Here, we present quantitative Oblique Back- illumination Microscopy (qOBM) as a novel, label-free imaging technique for real-time, non-invasive monitoring of GBM spheroids treated with tumor targeting chimeric antigen receptor T-cells (CAR T-cells). qOBM overcomes existing imaging limitations by providing high-resolution, 3D quantitative phase imaging through epi-illumination, enabling longitudinal visualization of cellular and subcellular processes within thick spheroids. Here, we apply qOBM to monitor the responses of GBM spheroids derived from three unique patient cell lines to targeted CAR T-cell immunotherapy and non-targeted controls. With this, we capture changes in the spheroids over 72 hours of treatment, allowing for visualization of processes such as CAR T-cell infiltration, mitosis, and apoptosis. Further, using images from GBM/CAR T cell cocultures, we develop a machine learning model for predicting spheroid cytotoxicity rates. Our findings establish qOBM as a powerful, non-destructive tool for longitudinal GBM spheroid toxicity monitoring and demonstrate its potential to advance personalized cancer therapy by providing real-time insight into treatment efficacy. © 2025 SPIE.

关键词： T-cells

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Manufacturing strategies for highly sensitive and self-powered piezoelectric and triboelectric tactile sensors

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International Journal of Extreme Manufacturing 2025年第1期7卷 151-172页

作者： Hyosik Park Gerald Selasie Gbadam Simiao Niu Hanjun Ryu Ju-Hyuck Lee Department of Energy Science and Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988Republic of Korea Department of Biomedical Engineering Rutgers UniversityPiscatawayNJ 08854United States of America Department of Advanced Materials Engineering Chung-Ang UniversityAnseong 17546Republic of Korea Department of Intelligence Energy and Industry Chung-Ang UniversitySeoul 06974Republic of Korea Energy Science and Engineering Research Center Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988Republic of Korea

Piezoelectric and triboelectric effects are of growing interest for facilitating high-sensitivity and self-powered tactile sensor *** working principles of piezoelectric and triboelectric nanogenerators provide strategies for enhancing output voltage signals to achieve high *** the piezoelectric constant and surface triboelectric charge density are key factors in this *** such as annealing processes,doping techniques,grain orientation controls,crystallinity controls,and composite structures can effectively enhance the piezoelectric *** increasing triboelectric output,surface plasma treatment,charge injection,microstructuring,control of dielectric constant,and structural modification are effective *** fabrication methods present significant opportunities in tactile sensor *** review article summarizes the overall piezoelectric and triboelectric fabrication processes from materials to device *** highlights applications in pressure,touch,bending,texture,distance,and material recognition *** conclusion section addresses challenges and research opportunities,such as limited flexibility,stretchability,decoupling from multi-stimuli,multifunctional sensors,and data processing.

关键词： triboelectric piezoelectric tactile sensor manufacturing composite

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Brain functional connectivity network during deception: a visibility graph approach

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The European Physical Journal Special Topics 2025年 1-14页

作者： Rahimi Saryazdi, Ali Bayani, Atiyeh Ghassemi, Farnaz Rajagopal, Karthikeyan Department of Biomedical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran Center for Research SRM Easwari Engineering College Chennai India Center for Cognitive Science Trichy SRM Medical College Hospital and Research Center Trichy India Center for Research SRM TRP Engineering College Trichy India

Deception is a complex cognitive process involving coordinated activity across multiple brain regions. The detection of deception is vital in various fields, from forensic investigations to cognitive neuroscience. This study proposes a novel method for investigating brain functional connectivity in the context of deception detection. The brain functional connectivity network is constructed by correlating the degree sequences of visibility graphs (VG) derived from 33 EEG channels. Four graph-based features, consisting of average and deviation of strength, clustering coefficient, and modularity, are extracted from the constructed networks. A threshold is then applied to the weighted functional networks to compute binary networks. Additionally, three features based on average centrality (average degree centrality, average closeness centrality, and average betweenness centrality) are also extracted. Statistical analysis reveals significant differences between the extracted features, highlighting the effectiveness of the VG method in capturing the underlying brain dynamics involved in deception. It has been observed that while the local networks in the truth mode exhibit higher average degree compared to the lying mode, the degree values in the lying mode are more closely clustered, leading to a higher average degree in the lying mode. Moreover, the investigation of dynamic functional networks over time shows higher connectivity during deception compared to truth. Specific regions exhibit increased connectivity during deception, indicating that certain brain areas are more actively engaged in deceptive behavior. This novel approach introduces a new perspective on brain connectivity during deceptive behavior, with potential applications in future neuroscience research and practical implementations in deception detection.

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Association analysis of an anti-obesity mechanism and key ripened Pu-erh tea bioactive components by mimicking human general tea drinking

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Food Science and Human Wellness 2025年第2期14卷 450-468页

作者： Junyu Liu Zhengyang Song Haihong Chen Wen Zeng Guirong Han Wei Li Bing Xu Yuan Lu Canyang Zhang Zhenglian Xue Bin Lü Chong Zhang Song Yang Yi Wang Xinhui Xing MOE Key Laboratory for Industrial Biocatalysis Centre for Synthetic and Systems BiologyDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 518055China Anhui University of Technology Maanshan 243002China Yunnan Shujian Tea Co. Ltd.Kunming 650000China Shandong Province Key Laboratory of Applied Mycology Qingdao International Center on Microbes Utilizing BiogasSchool of Life SciencesQingdao Agricultural UniversityQingdao 266109China

Pu-erh tea,a traditional Chinese beverage,performs an anti-obesity function,but the correlation between its components and efficacy remains ***,we screened two Pu-erh teas with significant anti-obesity efficacies from 11 *** vitro experiments revealed that lipid accumulation in L02 cells and lipid synthesis in 3T3-L1 cells were significantly better inhibited by Tea-B than *** in vivo experiments using model mice revealed that the differences in chemical components generated two pathways in the anti-obesity efficacy and mechanism of Pu-erh ***-A changes the histomorphology of brown adipose tissue(BAT)and increases the abundance of Coriobacteriaceae_UCG_002 and cyclic AMP in guts through high chemical contents of cyclopentasiloxane,decamethyl,tridecane and 1,2,3-trimethoxybenzene,eventually increasing BAT activation and fat browning gene expression;the high content of hexadecane and 1,2-dimethoxybenzene in Tea-B reduces white adipose tissue(WAT)accumulation and the process of fatty liver,increases the abundance of Odoribacter and sphinganine 1-phosphate,inhibits the expression of lipid synthesis and transport *** mechanistic findings on the association of the representative bioactive components in Pu-erh teas with the anti-obesity phenotypes,gut microbes,gut metabolite structure and anti-obesity pathways,which were obtained for the first time,provide foundations for developing functional Pu-erh tea.

关键词： Anti-obesity Bioactive components Lipid metabolism Multiomics analysis Pu-erh tea

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Federated Meta Continual Learning for Efficient and Autonomous Edge Inference 24th

Federated Meta Continual Learning for Efficient and Autono...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Li, Bingze Ho, Stella Qu, Youyang Xu, Chenhao Luan, Tom H. Gao, Longxiang Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Department of Biomedical Engineering The University of Melbourne VIC Melbourne Australia School of Information Technology Deakin University VIC Geelong Australia School of Cyber Engineering Xidian University Xi’an China

ISBN: (纸本)9789819615476

With an increasing volume of data being collected and processed on edge, Federated Learning (FL) has become a dominant approach to train shared global models on distributed data held by diverse edge clients without exposing privacy. However, with expectations of high-quality user experience, instantaneous intelligent decisions must be made at the network edge to meet performance, security, and latency requirements. Intuitively, this challenge becomes more daunting as edge devices are constrained by limited computing and storage resources. Furthermore, edge clients need to continuously acquire, update, accumulate, and apply knowledge in domains requiring the processing of sensitive data and long-term model training. It has been proven that edge clients often forget previous tasks knowledge after learning new tasks, resulting in catastrophic forgetting. To mitigate this, we propose a Federated Meta Continual Learning (FMCL) approach. It requires edge clients not only to learn new tasks quickly but also to memorize rapidly. Specifically, we adopted a MAML (Model-Agnostic Meta-Learning) framework with memory replay, setting up buffers at edge clients to consolidate old tasks. In such a way, the model learns optimal initialization to quickly adapt to all seen tasks while preventing catastrophic forgetting. Extensive evaluation results indicate that FMCL performs well in alleviating catastrophic forgetting and achieves a good balance between learning new tasks and remembering existing tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Multi-Scale Feature Fusion with Image-Driven Spatial Integration for Left Atrium Segmentation from Cardiac MRI Images

arXiv

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arXiv 2025年

作者： Kundu, Bipasha Yang, Zixin Simon, Richard Linte, Cristian Center for Imaging Science Rochester Institute of Technology RochesterNY14623 United States Department of Biomedical Engineering Rochester Institute of Technology NY14623 United States

Accurate segmentation of the left atrium (LA) from late gadolinium-enhanced magnetic resonance imaging plays a vital role in visualizing diseased atrial structures, enabling the diagnosis and management of cardiovascular diseases. It is particularly essential for planning treatment with ablation therapy, a key intervention for atrial fibrillation (AF). However, manual segmentation is time-intensive and prone to inter-observer variability, underscoring the need for automated solutions. Class-agnostic foundation models like DINOv2 have demonstrated remarkable feature extraction capabilities in vision tasks. However, their lack of domain specificity and task-specific adaptation can reduce spatial resolution during feature extraction, impacting the capture of fine anatomical detail in medical imaging. To address this limitation, we propose a segmentation framework that integrates DINOv2 as an encoder with a UNet-style decoder, incorporating multi-scale feature fusion and input image integration to enhance segmentation accuracy. The learnable weighting mechanism dynamically prioritizes hierarchical features from different encoder blocks of the foundation model, optimizing feature selection for task relevance. Additionally, the input image is reintroduced during the decoding stage to preserve high-resolution spatial details, addressing limitations of downsampling in the encoder. We validate our approach on the LAScarQS 2022 dataset and demonstrate improved performance with a 92.3% Dice and 84.1% IoU score for giant architecture compared to the nnUNet baseline model. These findings emphasize the efficacy of our approach in advancing the field of automated left atrium segmentation from cardiac MRI. © 2025, CC BY.

关键词： Magnetic resonance imaging

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Developing a Multi-site Hyperscanning Procedure for Investigating Interbrain Synchrony Underlying Remote Social Interaction 17th

Developing a Multi-site Hyperscanning Procedure for Investig...

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17th International Conference on Brain Informatics, BI 2024

作者： Limtragooltongchai, Sirapakit Yamtuan, Kawin Gracia, Javier O. Chunharas, Chaipat Sriravanasan, Ramesh Chaisilprungraung, Thitaporn Itthipuripat, Sirawaj Neuroscience Center for Research and Innovation King Mongkut’s University of Technology Thonburi Bangkok Thailand Institute of Field Robotics King Mongkut’s University of Technology Thonburi Thonburi Thailand DEVCOM Army Research Laboratory Humans in Complex Systems Division AdelphiMD United States Chula Neuroscience Center King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok10330 Thailand Cognitive Clinical and Computational Neuroscience Department of Internal Medicine Faculty of Medicine Chulalongkorn University Bangkok10330 Thailand Department of Cognitive Sciences University of California IrvineCA United States Department of Biomedical Engineering University of California IrvineCA United States Department of Computer Engineering King Mongkut’s University of Technology Thonburi Bangkok10600 Thailand

ISBN: (纸本)9789819632930

EEG hyperscanning provides novel insights into inter-brain connectivity during social interactions by enabling the simultaneous recording of neural activity from multiple individuals. This research aims to develop and validate a new protocol in which dyads engage in a synchronized button-pressing task across both same-location and multi-location setups. Our findings reveal significantly higher interpersonal neural synchronization during the interaction period compared to the baseline. Notably, the increased neural synchronization is comparable across the same- and multi-location setups, spanning frontal, central, and posterior electrodes. Interestingly, the level of synchronization in the multi-location setup is greater than in the same-location setup over electrodes positioned above the right superior temporal gyrus (STG), a region associated with social cognition and the mirror neuron system (MNS). These findings validate our methodology for studies across different locations and open new avenues for research into inter-brain synchronization in remote environments. Our experimental protocol could enhance the design of experiments and applications involving social interaction, particularly in remote settings, which have gained popularity due to COVID-19. It also advances our understanding of the neural mechanisms that support social communication in the new normal era. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Economic and social effects

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