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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Carluccio, Giuseppe Collins, Christopher M. Riccio, Daniele Miranda, Vincenzo Ruello, Giuseppe Department of Electrical Engineering and Information Technology University of Napoli Federico II Italy Bernard and Irene Schwartz Center for Biomedical Imaging Department of Radiology New York University School of Medicine New YorkNY United States

ISBN: (纸本)9781946815200

High-Permittivity Materials (HPM) are used in MRI to improve the radiofrequency B1 field, resulting in an increase of the SNR and of the transmit efficiency in the tissues. In a previous study, it was shown that the field can be enhanced even more when, instead of a single HPM layer, a multilayer dielectric structure is used. This result was obtained with the optimization of the permittivity of the HPM layers with the fields calculated with a 2D cylindrical analytical solution. Since analytical solutions represent geometries that are not very heterogeneous and complex such as human tissues, in this study we have repeated the optimization with data computed with 3D numerical simulations. The fields were transmitted with a dipole to excite the head of a numerical body model surrounded by spherical dielectric shells. This study confirms that multilayer dielectric shells can enhance the field even more than a single HPM layer, with the improvement quantified as about 6.5%. However, even if multilayer solutions can enhance the signal, their construction could face manufacturing challenges. © 2025 USNC-URSI.

关键词： Tissue

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Deep Learning Networks to Estimate Electric Fields From Noisy B1 Maps

Deep Learning Networks to Estimate Electric Fields From Nois...

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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Carluccio, Giuseppe Montin, Eros Collins, Christopher M. Lattanzi, Riccardo Riccio, Daniele Ruello, Giuseppe Department of Electrical Engineering and Information Technology University of Napoli Federico II Italy Bernard and Irene Schwartz Center for Biomedical Imaging Department of Radiology New York University School of Medicine New YorkNY United States

ISBN: (纸本)9781946815200

Deep learning networks have shown promising results in estimating electric fields from B1 maps. Some recent studies have shown that 2D analytical solutions can quickly generate data to be used as potential data augmentation with numerically simulated data. Since the ultimate goal is to have the developed deep learning networks able to operate with experimentally acquired data which might be affected by noise, in this study we have developed and tested the ability of these 2D networks to accurately predict the electric fields from noisy B1 maps. The networks could predict well the electric fields also in presence of noise, with a maximum NRMSE of 13.6%. © 2025 USNC-URSI.

关键词： Analytical Solutions Deep Learning MRI Multilayer Noise

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EA-SoGripper: Electroadhesion-Stiffening Self-Adaptive Soft Robotic Gripper

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IEEE/ASME Transactions on Mechatronics 2025年

作者： Xiong, Quan Li, Dannuo Li, Xianglong Liu, Lina Zhou, Xuanyi Ju, Haotian Zhu, Yanhe Yeow, Raye Chen-Hua National University of Singapore Department of Biomedical Engineering 117583 Singapore Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

This article introduces the electroadhesion-stiffening self-adaptive soft robotic gripper (EA-SoGripper), a novel solution to the limitations of traditional rigid robotic grippers. The EA-SoGripper leverages electroadhesion (EA) clutches to dynamically adjust the tension of films, enabling adaptive grasping for objects of varying shapes, sizes, weights, and stiffness. By controlling the applied voltage, the gripper achieves tunable grasping stiffness, with a range of 0.06–1.25 N/mm. A mathematical model predicting load capacity as a function of stiffness and input voltage offers theoretical guidance for practical applications. The gripper integrates a real-time force sensor and a feedback control algorithm, achieving grasping force regulation with high precision. A portable, low-cost ($130), and lightweight (197 g) ac high-voltage power supply system, with a fast response time of 75 ms, further enhances its versatility. Experimental validation demonstrates the EA-SoGripper's ability to securely grasp objects with diverse geometries, including fragile and delicate items, while adapting stiffness to support up to 400 g loads. These results highlight the gripper's potential for applications requiring precise and adaptive handling. © 1996-2012 IEEE.

关键词： Robotic arms

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Transfer learning‑based attenuation correction in ^99mTc-TRODAT-1 SPECT for Parkinson’s disease using realistic simulation and clinical data

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EJNMMI Physics 2025年第1期12卷 1-14页

作者： Huang, Wenbo Jiang, Han Du, Yu Wang, Haiyan Sun, Hao Hung, Guang-Uei Mok, Greta S. P. Biomedical Imaging Laboratory (BIG) Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau SAR Taipa Macao PET-CT Center Fujian Medical University Union Hospital Fuzhou China Center for Cognitive and Brain Sciences Institute of Collaborative Innovation University of Macau SAR Taipa Macao Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Biomedical Engineering Southern Medical University Guangzhou China Department of Nuclear Medicine Chang Bing Show Chwan Memorial Hospital Changhua County Taiwan

Purpose: Dopamine transporter (DAT) SPECT is an effective tool for early Parkinson’s disease (PD) detection and heavily hampered by attenuation. Attenuation correction (AC) is the most important correction among other corrections. Transfer learning (TL) with fine-tuning (FT) a pre-trained model has shown potential in enhancing deep learning (DL)-based AC methods. In this study, we investigate leveraging realistic Monte Carlo (MC) simulation data to create a pre-trained model for TL-based AC (TLAC) to improve AC performance for DAT SPECT. Methods: A total number of 200 digital brain phantoms with realistic ^99mTc-TRODAT-1 distribution was used to generate realistic noisy SPECT projections using MC SIMIND program and an analytical projector. One hundred real clinical ^99mTc-TRODAT-1 brain SPECT data were also retrospectively analyzed. All projections were reconstructed with and without CT-based attenuation correction (CTAC/NAC). A 3D conditional generative adversarial network (cGAN) was pre-trained using 200 pairs of simulated NAC and CTAC SPECT data. Subsequently, 8, 24, and 80 pairs of clinical NAC and CTAC DAT SPECT data were employed to fine-tune the pre-trained U-Net generator of cGAN (TLAC-MC). Comparisons were made against without FT (DLAC-MC), training on purely limited clinical data (DLAC-CLI), clinical data with data augmentation (DLAC-AUG), mixed MC and clinical data (DLAC-MIX), TL using analytical simulation data (TLAC-ANA), and Chang’s AC (ChangAC). All datasets used for DL-based methods were split to 7/8 for training and 1/8 for validation, and a 1-/2-/5-fold cross-validation were applied to test all 100 clinical datasets, depending on the numbers of clinical data used in the training model. Results: With 8 available clinical datasets, TLAC-MC achieved the best result in Normalized Mean Squared Error (NMSE) and Structural Similarity Index Measure (SSIM) (TLAC-MC;NMSE = 0.0143 ± 0.0082/SSIM = 0.9355 ± 0.0203), followed by DLAC-AUG, DLA

关键词： 99mTc-TRODAT-1 Attenuation correction Brain SPECT Monte carlo simulation Parkinson’s disease Transfer learning

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Liposome of a synergistic combination of HDP-mimicking polymer and rifampicin for treating bacterial infections in aquaculture via oral administration

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Science China Materials 2025年第4期68卷 1259-1270页

作者： Haowen Yu Luhang Chen Yueming Wu Wenhui Dai Minzhang Chen Yuan Chen Longqiang Liu Jiangzhou Wang Xinqi Huang Kang Chen Runhui Liu State Key Laboratory of Bioreactor Engineering East China University of Science and TechnologyShanghai 200237China Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism Key Laboratory for Ultrafine Materials of Ministry of EducationFrontiers Science Center for Materiobiology and Dynamic ChemistryEngineering Research Center for Biomedical Materials of Ministry of EducationSchool of Materials Science and EngineeringEast China University of Science and TechnologyShanghai 200237China Department of Biomaterials and Stem Cells Suzhou Institute of Biomedical Engineering and TechnologyChinese Academy of SciencesSuzhou 215163China

The extensive use of antibiotics in high-density aquaculture has accelerated the emergence of antibiotic-resistant *** presence of antibiotics in water and soil,and their transmission through the food chain exacerbate the pressures associated with antibiotic resistance,posing a significant threat to human *** this challenge and serious issue,effective alternatives to antibiotics remain *** this study,we report a potent synergistic effect between an HDP-mimicking polymer,DLLys90-BLG10,and rifampicin against Vibrio *** synergistic combination substantially reduces the required dosage of rifampicin,thereby mitigating the risk of antibiotic resistance development and the release of rifampicin into water and ***,we developed a cell-penetrating peptide-modified liposome system that can co-encapsulate DLLys90-BLG10 and rifampicin,which exerts potent antibacterial activity against Vibrio both in vitro and in vivo,while maintaining ***,oral administration of CPP-Lip@Syn showed effective control of Vibrio *** strategy opens new avenues in exploring antibiotic alternatives in aquaculture and implies potential applications in aquaculture.

关键词： liposomes oral administration aquaculture synergistic combinations Vibrio infections

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Real-Time Health Monitoring and Tracking System

Real-Time Health Monitoring and Tracking System

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International Conference on Biosignals, Images and Instrumentation (ICBSII)

作者： V.S Shelma Vincent D Amala Hepzibha D Hepsiba L.D. Vijay Anand Department of Biomedical Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu Department of Robotics Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India

ISBN: (数字)9798331513863

ISBN: (纸本)9798331513870

Health monitoring has become an essential system in modern healthcare for tracking real-time vital parameters. This device offers a cost-effective health monitoring solution with a live tracking feature, using an Arduino Uno (microcontroller) integrated with various sensors, including the DHT11 for temperature measurement, which also tracks the environmental humidity level. Additionally, the system incorporates the GY-NEO6MV2 (GPS module) for location tracking, which is particularly useful for tracking patient with medical condition and the AD8232 (ECG sensor) for continuous heart rate monitoring of the patient. The system features an LED-based alert mechanism, which activates to signal abnormal conditions detected by the DHT11 sensor, particularly temperature-related anomalies. This device also has a panic button which helps the individual to notify the caretakers or healthcare providers when they experience any abnormality. Arduino Uno processes all the data collected from these sensors and presents it effectively. The obtained data is collected by the Thing speak app through real-time. The GPS module also helps to pinpoint the patient’s location, making the system ideal for health monitoring applications such as elder care or remote patient management. The system can be monitored remotely, which reduces the frequent visit of the caretaker or healthcare professionals and helps with the update of the patient through real-time. With its portability and affordability, this system stands out as a highly practical and cost-efficient option, enabling easy and continuous patient monitoring from anywhere.

关键词： Temperature sensors Temperature measurement Heart rate Microcontrollers Humidity Electrocardiography Real-time systems Sensor systems Monitoring Global Positioning System

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pH-responsive AIE nanogels for synergistic chemo-photodynamic cancer therapy with imaging guidance

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Science China Chemistry 2025年第4期68卷 1445-1455页

作者： Yilin Zhu Liping Zhang Rongyuan Zhang Chenghan He Han Yang Yong Liu Ryan T.K.Kwok Jacky W.Y.Lam Jianwei Sun Jing Feng Zheng Zhao Cuiping Yao Ben Zhong Tang Institute of Biomedical Photonics and Sensing School of Life Science and TechnologyXi'an Jiaotong UniversityXi'an 710049China Clinical Translational Research Center of Aggregation-Induced Emission The Second Affiliated HospitalSchool of MedicineSchool of Science and EngineeringShenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)Shenzhen 518172China Department of Urology Jining NO.1 People's Hospital Jining 27200China AIE Institute Guangzhou 510530China Department of Chemistry the Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and ReconstructionDivision of Life ScienceState Key Laboratory of Molecular Neuroscienceand Department of Biological and Chemical EngineeringThe Hong Kong University of Science and TechnologyHong Kong 999077China

Photodynamic therapy(PDT)is a promising cancer treatment that uses photosensitizers(PSs)to generate cytotoxic reactive oxygen species(ROS)under light;but improving its efficacy is crucial for clinical *** address this;we propose a smart nanoplatform(P@BAO-DOX)for synergistic chemo-photodynamic therapy;featuring efficient PDT;controllable drug release;and fluorescence imaging *** designed an aggregation-induced emission(AIE)-based PS(BAO)with effective ROS generation and NIR-II ***;BAO as a PS and doxorubicin(DOX)as a chemo drug were encapsulated in p H-responsive nanogels(PNA)to obtain P@BAO-DOX *** uptake by tumor cells;the nanogel releases drugs in acidic conditions;leading to cell *** light irradiation further triggers BAO to produce substantial ROS;enhancing phototoxicity and synergistic chemo-PDT cancer ***;P@BAO-DOX nanogels;as a smart nanoplatform;offer precise drug release and efficient ROS generation for imaging-guided chemo-PDT synergistic therapy;showing promise in advancing cancer treatment.

关键词： photodynamic therapy aggregation-induced emission pH-responsive nanogels imaging-guided synergistic cancer therapy

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Topology entropy: Enhancing graph partitioning for TAD identification and single-cell clustering

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Computational and Structural Biotechnology Journal 2025年 27卷 1864-1886页

作者： Liang, Qiushi Zhao, Shengjie Chen, Lingxi Li, Shuai Cheng School of Computer Science and Technology Tongji University Shanghai201804 China Department of Computer Science City University of Hong Kong 999077 Hong Kong Department of Biomedical Sciences City University of Hong Kong 999077 Hong Kong Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of Education China

Entropy quantifies the limits of information compression and provides a theoretical foundation for exploring complex structures in large-scale graphs. However, effective metrics are needed to capture the intricate structural details in biological graphs. In this paper, we introduce the topology entropy encoding tree to quantify the complexity of biological graphs and show that minimizing the associated entropy is equivalent to optimal graph partitioning. We develop two methods, TEC-O and TEC-U, for partitioning ordered and unordered biological graphs. TEC-O is applied to identify Topologically Associated Domains (TADs) in Hi-C contact maps, while TEC-U is used for cell clustering in single-cell sequencing data. Results from simulated datasets demonstrate that topology entropy is robust to noise and effectively captures structural information, outperforming existing methods. Experiments on Hi-C data from five cell lines and ten single-cell sequencing datasets show that TEC-O and TEC-U achieve the highest accuracy in TAD detection and cell clustering, respectively, providing biologically meaningful insights. © 2025 The Authors

关键词： Cell culture

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不锈钢-铜复合箔材微拉深成形性能的模拟和实验研究（英文）

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Journal of Central South University 2025年第04期32卷 1237-1251页

作者：齐艳阳马晓光姜正义马丽楠王志华周存龙 HASAN Mahadi DOBRZA?SKI Leszek A. 赵敬伟 College of Mechanical Engineering Taiyuan University of Technology Engineering Research Center of Advanced Metal Composites Forming Technology and Equipment(Ministry of Education) School of Mechanical Materials Biomedical and Mechatronic Engineering University of Wollongong School of Mechanical Engineering Taiyuan University of Science and Technology Department of Industrial and Production Engineering American International University Bangladesh Medical and Dental Engineering Center for Research Design and Production ASKLEPIOS

在本研究中，将厚度为50μm的双层不锈钢-铜复合箔材分别在800、900和1000℃下退火5 min，以获得不同的微观组织结构。研究退火温度对不锈钢-铜复合箔材成形性能和微拉深件表面质量的影响，并分析了其成形机制，开发了基础模型、Vorono... 详细信息

在本研究中，将厚度为50μm的双层不锈钢-铜复合箔材分别在800、900和1000℃下退火5 min，以获得不同的微观组织结构。研究退火温度对不锈钢-铜复合箔材成形性能和微拉深件表面质量的影响，并分析了其成形机制，开发了基础模型、Voronoi模型和表面形貌模型用于分析不锈钢-铜复合箔材微拉深过程中的成形性能。结果表明，900℃退火的不锈钢-铜复合箔材的微观组织均匀且细化，因而表现出最佳的塑性。在微拉深过程中，拉深力随退火温度的升高而降低。900℃退火试样成形的微拉深件起皱较少，壁厚分布较均匀，表面质量较高。与基础模型和Voronoi模型相比，考虑材料不均匀性和表面形貌的表面形貌模型与实验结果最接近。

关键词：微拉深退火温度不锈钢-铜复合箔材成形性能起皱有限元方法

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Cryopreservable, scalable and ready-to-use cell-laden patches for diabetic ulcer treatment

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Bioactive Materials 2025年 50卷 461-474页

作者： Yu, Bangrui Peng, Lanlan Dang, Wenjun Fu, Ying Li, Zhijie Feng, Jinteng Zhao, Heng Wang, Tian Xu, Feng Yarmush, Martin L. Huang, Haishui The Key Laboratory of Biomedical Information Engineering of Ministry of Education Xi'an Jiaotong University Shaanxi Xi'an 710049 China Bioinspired Engineering and Biomechanics Center (BEBC) School of Life Science and Technology Xi'an Jiaotong University Shaanxi Xi'an 710049 China Department of Thoracic Surgery The First Affiliated Hospital of Xi'an Jiaotong University Xi'an 710049 China Center for Engineering in Medicine and Surgery Massachusetts General Hospital Harvard Medical School and Shriners Hospitals for Children Boston 02114 MA United States Department of Biomedical Engineering Rutgers University Piscataway 08854 NJ United States

Stem cell-laden hydrogel patches are promising candidates to treat chronic ulcers due to cells’ long-lasting and dynamic responses to wound microenvironment. However, their clinical translations are prohibited by the cryopreservation difficulty due to their weak mechanical strength and slow biotransport capability, and by the morphological mismatch between clinical ulcers and pre-fabricated patches. Here we report a stem cell-laden alginate-dopamine hydrogel patch that can be readily cryopreserved, processed, and scaled toward clinical usages. This cell-hydrogel patch not only maintains cell viability and structure integrity during cryopreservation, but also can be directly utilized without centrifugation or incubation post cryopreservation. In addition, this tissue-adhesive hydrogel patch enables close wound contact and fast cellular response, and its scalable and flexible structure enables assembly for large or irregularly shaped ulcers. Therefore, it accelerates ulcer healing and reduces scar formation via continuous, versatile, self-adjusting paracrine of imbedded, cryopreserved stem cells. These findings highlight its potential for scalable clinical applications in chronic wound management and pave the way for broader adoption of ready-to-use regenerative therapies. © 2025 The Authors

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