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Mussel-inspired sulfated hyaluronan cryogel patch with antioxidant, anti-inflammatory, and drug-loading properties for multifunctional wound adhesives

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Bioactive Materials 2024年第10期40卷 582-596页

作者： Wonmoon Song Young Hwan Choi Young Gi Moon Changyub Lee M.Nivedhitha Sundaram Nathaniel S.Hwang School of Chemical and Biological Engineering Institute for Chemical ProcessesSeoul National UniversitySeoul08826Republic of Korea Interdisciplinary Program in Bioengineering Seoul National UniversitySeoul08826Republic of Korea Bio-MAX/N-Bio Institute Institute of BioEngineeringSeoul National UniversitySeoul08826Republic of Korea Division of Pediatric Cardiac Surgery Department of SurgeryJohns Hopkins School of MedicineBaltimoreMDUSA Institute of Engineering Research Seoul National UniversitySeoul08826Republic of Korea

Wounds, characterized by the disruption of the continuity of body tissues resulting from external trauma,manifest in diverse types and locations. Although numerous wound dressings are available for various woundscenarios, it remains challenging to find an integrative wound dressing capable of addressing diverse woundsituations. We focused on utilizing sulfated hyaluronan (sHA), known for its anti-inflammatory properties andcapacity to load cationic drugs. By conjugating catechol groups to sHA (sHA-CA), we achieved several advantagesin wound healing: 1) Fabrication of patches through crosslinking with catechol-modified high-molecularweighthyaluronan (HA(HMW)-CA), 2) Adhesiveness that enabled stable localization, 3) Radical scavenging thatcould synergize with the immunomodulation of sHA. The sHA-CA patches demonstrated therapeutic efficacy inthree distinct murine wound models: diabetic wound, hepatic hemorrhage, and post-surgical adhesion. Collectively,these findings underscore the potential of the sHA-CA patch as a promising candidate for the nextgenerationwound dressing.

关键词： Adhesive patch Anti-inflammation Sulfated hyaluronic acid Post-surgical adhesion Diabetic wound Hemostasis

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Evaluation of a 3D Position Sensitive Time-of-flight PET Detector Unit with CPLD-based Frontend Electronics

Evaluation of a 3D Position Sensitive Time-of-flight PET Det...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Z. Zhao H.S. Shim C. Levin Radiology Department Stanford University Stanford California United States of America Seoul National University Interdisciplinary program of bioengineering Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

This study introduces and evaluates a stackable side-readout detector unit with second-generation frontend electronics for near 100 ps CTR Time-of-Flight 3D Position Sensitive (TOF-3DPS) detectors. This design utilizes a timing signal multiplexing scheme based on RF amplifiers and summing circuits to achieve 24:1 timing multiplexing and employs complex programmable logic devices (CPLDs) to facilitate high-precision energy measurement, and photon depth of interaction (DOI) positioning for single and multi-interaction inter-crystal scatter (ICS) events across different crystal elements within a detector unit. Experimental results with a single layer sub-unit comprising a $4 \times 2$ array of $3 \times 3 \times 10 \mathrm{~mm}^{3}$ LYSO:Ce crystals side-coupled with a $4 \times 6$ array of $3.16 \times 3.16 \mathrm{~mm}^{2}$ SiPMs yielded a 9.88 ± 0.86% energy resolution and a Coincidence Timing Resolution (CTR) of $121.28 \pm 3.35$ ps FWHM. Electrical collimation measurements performed at different positions along the 10 mm length of one crystal element produced a $1.44 \pm 0.44 \mathrm{~mm}$ FWHM DOI resolution. Additionally, electronic collimation of different columns in a detector unit revealed ICS event ratios for scatter to adjacent columns from the collimated column of 6.90%, 10.46%, 10.85%, and 5.33%, respectively. The side-readout detector layer sub-unit and the corresponding frontend circuitry have a footprint of only $27 \mathrm{~mm} \times 95 \mathrm{~mm}$, making it easy to stack and form a multi-layer TOF-3DPS block detector.

关键词： Multiplexing Temperature sensors Semiconductor device measurement Three-dimensional displays Semiconductor detectors Energy resolution Summing circuits

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SwiftMedSAM: An Ultra-lightweight Prompt-Based Universal Medical Image Segmentation Model for Highly Constrained Environments 1

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International Challenge on Segment Anything in Medical Images on Laptop held in conjunction with the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024

作者： Kong, Youngbin Kim, Kwangtai Jeong, Seoi Lee, Kyu Eun Kong, Hyoun-Joong Interdisciplinary Program in Bioengineering Graduate School Seoul National University Seoul Korea Republic of Department of Transdisciplinary Medicine Seoul National University Hospital Seoul Korea Republic of Department of Surgery Seoul National University Hospital and College of Medicine Seoul Korea Republic of Department of Medicine Seoul National University College of Medicine Seoul Korea Republic of Innovative Medical Technology Research Institute Seoul National University Hospital Seoul Korea Republic of Interdisciplinary Program of Medical Informatics Seoul National University College of Medicine Seoul Korea Republic of

ISBN: (数字)9783031818547

ISBN: (纸本)9783031818530

Medical image segmentation is a crucial step for accurate diagnosis and treatment planning, as it provides quantitative information about anatomical structures and pathological lesions in various clinical scenarios. However, the existing methodologies have limitations in terms of their generalizability and computational efficiency. In this study, we propose SwiftMedSAM, an ultra-lightweight prompt-based general model, to enable efficient medical image segmentation even in resource-constrained environments. Based on LiteMedSAM, we significantly reduced the model size and computational complexity through the hyperparameter optimization of the image encoder and mask decoder components. SwiftMedSAM showed remarkable performance across various imaging modalities enabling real-time inference in resource-limited computing environments. It achieved a validation score of 0.75 demonstrating that SwiftMedSAM outperformed the existing methodologies in terms of the trade-off between accuracy and efficiency. Owing to its unprecedented generalizability and low computational cost, SwiftMedSAM is expected to enable high-quality medical image analysis in resource-constrained settings, thereby contributing to advancements in precision medicine and telemedicine. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Medical imaging

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Slit-Wall Differentiation Method for Depth-of-Interaction Measurement for PET

Slit-Wall Differentiation Method for Depth-of-Interaction Me...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： D. Lee H. Hemmati M. Yi S.I. Kwon University of California Davis Biomedical Engineering Davis California United States of America Seoul National University Interdisciplinary Program in Bioengineering College of Engineering Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In positron emission tomography (PET), accurately measuring the Depth-of-Interaction (DOI) of 511 keV gamma ray interactions is essential for improving spatial resolution in small animal PET, especially at off-center detector positions. DOI resolution can be improved by modifying crystal structures, reflectors, or by using dual readout techniques. Most methods, except for the more electronics-intensive dual side readout, increase light sharing among pixels, thereby reducing photon availability per pixel. This study introduces a novel Slit-Wall Differentiation (SWD) method, designed to restrict light sharing to just four adjacent pixels, thus enhancing DOI accuracy. The SWD method involves placing strategic slits on the adjacent faces of each pixel, controlling light sharing depending on the DOI position. DOI information is calculated from the output patterns of Silicon Photomultiplier (SiPM) arrays. The effectiveness of the proposed method was validated through GATE simulations (vGATE 9.2) using a $3 \times 3$ Lutetium-Yttrium Oxyorthosilicate (LYSO) array with enhanced specular reflectors (ESRs). An LYSO array fabricated based on the proposed configuration was successfully prepared. For practical validation, an experimental setup using a 4 $\times 4$ NUV-HD-MT (Broadcom) SiPM array is also configured.

关键词： Temperature measurement Photomultipliers Semiconductor device measurement Semiconductor detectors Position measurement Silicon Positron emission tomography

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FPGA-Based Single-Input Time-to-Digital Converter with Rise Time Correction and Sub-2 ps Resolution for Precision Timing Applications

FPGA-Based Single-Input Time-to-Digital Converter with Rise ...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： D. Lee M. Yi S.I. Kwon Biomedical Engineering University of California Davis Davis California United States of America Seoul National University Interdisciplinary Program in Bioengineering College of Engineering Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In numerous fields, including physics, industry, and medical technology, the precise measurement of extremely short time intervals, such as those below 100 ps, is essential. This research introduces an innovative FPGA-based time-to-digital converter (TDC) implemented on the UltraScale+ platform (VCU118, Xilinx). The UltraScale+ platform improves upon timing resolution by incorporating a CARRY8 primitive cell as a delay element, an improvement over the CARRY4, which was widely used in previous platforms. Through the novel end-of-propagation (EOP) technique, the implemented TDC achieves an average bin size of 1.11 ps, demonstrating significant resource efficiency compared to other reported FPGA-based TDCs. This study details the design, implementation, and empirical validation of the TDC. Additionally, a unique feature of the proposed TDC is its ability to measure the input pulse width and apply rise time correction without requiring additional inputs. To demonstrate its practical applicability, the developed TDC was connected to the output of an ultrafast Cherenkov-Radiator-Integrated (CRI)-MCP-PMT after evaluating its electrical performance. The preliminary coincidence timing resolution of a pair of CRI-MCP-PMTs shows improvements from 107 ps to 73 ps (FWHM) with the proposed rise time correction. These advancements highlight the potential of the TDC not only for next-generation medical applications but also for its transformative impact in applications demanding ultra-precise timing.

关键词： Industries Semiconductor device measurement Microwave integrated circuits Image resolution Semiconductor detectors Pulse measurements Medical services

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RRED: A Radiology Report Error Detector based on Deep Learning Framework 4

RRED: A Radiology Report Error Detector based on Deep Learni...

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4th Workshop on Clinical Natural Language Processing, ClinicalNLP 2022

作者： Min, Dabin Kim, Kaeun Lee, Jong Hyuk Kim, Yisak Park, Chang Min Department of Radiology Seoul National University Hospital Korea Republic of Interdisciplinary Program in Bioengineering Seoul National University Graduate School Korea Republic of Department of Radiology Seoul National University College of Medicine Korea Republic of

ISBN: (纸本)9781955917773

Radiology report is an official record of radiologists’ interpretation of patients’ radiographs and it’s a crucial component in the overall medical diagnostic process. However, it can contain various types of errors that can lead to inadequate treatment or delay in diagnosis. To address this problem, we propose a deep learning framework to detect errors in radiology reports. Specifically, our method detects errors between findings and conclusion of chest X-ray reports based on a supervised learning framework. To compensate for the lack of data availability of radiology reports with errors, we develop an error generator to systematically create artificial errors in existing reports. In addition, we introduce a Medical Knowledge-enhancing Pre-training to further utilize the knowledge of abbreviations and key phrases frequently used in the medical domain. We believe that this is the first work to propose a deep learning framework for detecting errors in radiology reports based on a rich contextual and medical understanding. Validation on our radiologist-synthesized dataset, based on MIMIC-CXR, shows 0.80 and 0.95 of the area under precision-recall curve (AUPRC) and the area under the ROC curve (AUROC) respectively, indicating that our framework can effectively detect errors in the real-world radiology reports. © 2022 Association for Computational Linguistics.

关键词： Errors

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Single-cell RNA-sequencing and subcellular spatial transcriptomics facilitate the translation of liver microphysiological systems for regulatory application

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Journal of Pharmaceutical Analysis 2023年第7期13卷 691-693页

作者： Dan Li Zhou Fang Qiang Shi Nicholas Zhang Binsheng Gong Weida Tong Ahmet F.Coskun Joshua Xu Division of Bioinformatics and Biostatistics National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory UniversityAtlantaGA30332USA Machine Learning Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Division of Systems Biology National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Interdisciplinary Bioengineering Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Parker H.Petit Institute for Bioengineering and Bioscience Georgia Institute of TechnologyAtlantaGA30332USA

Reducing the use of animal models in drug development and safety assessment has long been supported by the *** and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals indicates that in 2020,experiments involved the use of over 100 million animals,with the United States leading the list by utilizing 20 million *** ethical considerations associated with animal testing and the costs in terms of time and money,animal models are not always effective in predicting human reactions to drug *** animal testing has been the traditional method for assessing the safety and efficacy of drugs.

关键词： money utilizing testing

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Cartilage targeting cationic peptide carriers display deep cartilage penetration and retention in a rabbit model of post-traumatic osteoarthritis

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Osteoarthritis and Cartilage 2025年第6期33卷 721-734页

作者： Boyer, Timothy L. Chao, Olivia Hakim, Bill Childress, Luke Meslier, Quentin A. Iyengar, Suhasini M. Ondrechen, Mary Jo Porter, Ryan M. Bajpayee, Ambika G. Department of Bioengineering Northeastern University Boston MA United States Department of Biochemistry Northeastern University Boston MA United States Graduate Program for Interdisciplinary Biomedical Sciences UAMS Little Rock AR United States Department of Chemistry and Chemical Biology Northeastern University Boston MA United States Department of Internal Medicine UAMS Little Rock AR United States Department of Orthopaedic Surgery UAMS Little Rock AR United States

Objective: Drug delivery to cartilage is limited by its complex architecture and avascularity. Cationic peptide carriers (CPCs) have previously been optimized for improved cartilage transport and retention of drugs in vitro. In this study, we evaluated the kinetics, stability, and immunogenicity of CPCs after a single intra-articular injection using a rabbit knee injury model. Design: New Zealand White rabbits were administered a single dose of Cy5-labeled CPCs in knees receiving anterior cruciate ligament transection (ACLT) or Sham surgery. CPC biodistribution and retention within joint tissues and synovial fluid were evaluated 1 and 7 days after administration, and extra-articular kinetics were assessed in serum. Histology, immunohistochemistry, and reverse transcription quantitative polymerase chain reaction were performed to assess synovitis and protease activity. Proteolytic analysis of CPCs in the presence of arthritic enzymes was evaluated using synovial fluid size-exclusion filtration, Fluorescence Resonance Energy Transfer analysis, and computational molecular docking. Results: CPCs penetrated the full depth of sulfated glycosaminoglycan (sGAG)-rich tissues, notably cartilage, and were retained through the latest timepoint measured (one week) in both Sham and ACLT knees. Compared to ACLT, Sham knees had greater joint retention at Day 1 (1.6-fold) and Day 7 (1.8-fold). CPC intra-tissue concentration strongly correlated with tissue sGAG density, which did not considerably differ between surgical conditions at these timepoints. However, CPCs exhibited elevated vascular clearance and proteolytic fragmentation in inflammatory conditions. CPCs did not increase macrophage abundance, cytokine expression, or alter tissue morphology. Conclusion: CPCs target the deep layers of cartilage, even in inflamed joints, and can be utilized to substantially improve intra-joint bioavailability of therapeutics. © 2025 Osteoarthritis Research Society International

关键词： Cartilage penetration Cationic carriers Charge-based drug delivery Post-traumatic osteoarthritis Rabbit

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COIN: Confidence Score-Guided Distillation for Annotation-Free Cell Segmentation

arXiv

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arXiv 2025年

作者： Jo, Sanghyun Lee, Seo Jin Lee, Seungwoo Hong, Seohyung Seo, Hyungseok Kim, Kyungsu OGQ Seoul Korea Republic of Laboratory of Cell & Gene Therapy Institute of Pharmaceutical Sciences College of Pharmacy Seoul National University Korea Republic of Department of Biomedical Science and Medical Research Center College of Pharmacy Seoul National University Korea Republic of School of Transdisciplinary Innovations Interdisciplinary Program in Bioengineering Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Cell instance segmentation (CIS) is crucial for identifying individual cell morphologies in histopathological images, providing valuable insights for biological and medical research. While unsupervised CIS (UCIS) models aim to reduce the heavy reliance on labor-intensive image annotations, they fail to accurately capture cell boundaries, causing missed detections and poor performance. Recognizing the absence of error-free instances as a key limitation, we present COIN (COnfidence score-guided INstance distillation), a novel annotation-free framework with three key steps: (1) Increasing the sensitivity for the presence of error-free instances via unsupervised semantic segmentation with optimal transport, leveraging its ability to discriminate spatially minor instances, (2) Instance-level confidence scoring to measure the consistency between model prediction and refined mask and identify highly confident instances, offering an alternative to ground truth annotations, and (3) Progressive expansion of confidence with recursive self-distillation. Extensive experiments across six datasets show COIN outperforming existing UCIS methods, even surpassing semi- and weakly-supervised approaches across all metrics on the MoNuSeg and TNBC datasets. The code is available at https://***/shjo-april/COIN. © 2025, CC BY.

关键词： Semantic Segmentation

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Bioceramic-mediated chondrocyte hypertrophy promotes calcified cartilage formation for rabbit osteochondral defect repair

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Bioactive Materials 2024年第10期40卷 306-317页

作者： Rachel H.Koh Junhee Kim Jeong-Uk Kim Seunghyun L.Kim Arun Kumar Rajendran Seunghun SLee Heesoo Lee Joo Hyun Kim Ji Hoon Jeong Yongsung Hwang Jong Woo Bae Nathaniel S.Hwang School of Chemical and Biological Engineering Institute of Chemical ProcessesSeoul National UniversitySeoul08826South Korea Interdisciplinary Program in Bioengineering Seoul National UniversitySeoul08826South Korea Department of Biomedical Engineering Dongguk UniversitySeoul10326South Korea Soonchunhyang Institute of Medi-bio Science(SIMS) Soonchunhyang UniversityCheonan31151South Korea Department of Integrated Biomedical Science Soonchunhyang UniversityAsan31538South Korea Department of Orthopaedic Surgery Konkuk University Chungju HospitalKonkuk University School of MedicineChungju27376South Korea BioMAX Institute Seoul National UniversitySeoul08826South Korea

Osteochondral tissue is a highly specialized and complex tissue composed of articular cartilage and subchondral bone that are separated by a calcified cartilage *** or gradient scaffolds,often in conjunction with stem cells and growth factors,have been developed to mimic the respective layers for osteochondral defect *** this study,we designed a hyaline cartilage-hypertrophic cartilage bilayer graft(RGD/RGDW)with ***,we demonstrated that RGD peptide-modified chondroitin sulfate cryogel(RGD group)is chondro-conductive and capable of hyaline cartilage ***,we incorporated whitlockite(WH),a Mg^(2+)-containing calcium phosphate,into RGD cryogel(RGDW group)to induce chondrocyte hypertrophy and form collagen X-rich hypertrophic *** is the first study to use WH to produce hypertrophic ***-laden RGDW cryogel exhibited significantly upregulated expression of hypertrophy markers in vitro and formed ectopic hypertrophic cartilage in vivo,which mineralized into calcified cartilage in bone ***,RGD cryogel and RGDW cryogel were combined into bilayer(RGD/RGDW group)and implanted into rabbit osteochondral defect,where RGD layer supports hyaline cartilage regeneration and bioceramic-containing RGDW layer promotes calcified cartilage *** the RGD group(monolayer)formed hyaline-like neotissue that extends into the subchondral bone,the RGD/RGDW group(bilayer)regenerated hyaline cartilage tissue confined to its respective layer and promoted osseointegration for integrative defect repair.

关键词： Bioceramic Whitlockite Bilayer scaffold Chondrocyte hypertrophy Osteochondral defect repair

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