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IEEE CPMT Symposium Japan

作者： Tadaaki Hoshi Nishiguchi Daichi Hisashi Kino Tetsu Tanaka Takafumi Fukushima Graduate School of Engineering Tohoku University Sendai Japan School of Engineering Tohoku University Sendai Japan Graduate School of Biomedical Engineering Tohoku University Sendai Japan Graduate School of Biomedical Engineering & Graduate School of Engineering Tohoku University Sendai Japan

This paper focuses on the fabrication of a PhotoBioModulation (PBM) device as a kind of flexible hybrid electronics (FHE) with a hydrogel substrate. PBM is a type of phototherapy using visible or near-infrared (NIR) light from LEDs or lasers. We propose an integrated PBM patch using RDL (redistribution layer)-first fan-out wafer-level packaging (FOWLP) with an array of embedded NIR mini-LEDs in the hydrogel as a substrate for chronic wound or bedsore healing. This paper characterizes the fan-out wirings formed on the hydrogel and describes multichip-to-wafer bonding with the mini-LEDs.

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Retaining spatial resolution multifocal confocal fluorescence microscopy with deep learning

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Optics Express 2025年第6期33卷 12288-12303页

作者： Suresh, Surag Athippillil Vyas, Sunil Yeh, J. Andrew Luo, Yuan Institute of Nano Engineering and Microsystems National Tsing Hua University Hsinchu30013 Taiwan Institute of Medical Device and Imaging National Taiwan University Taipei10051 Taiwan Program for Precision Health and Intelligent Medicine National Taiwan University Taipei106319 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10051 Taiwan YongLin Institute of Health National Taiwan University Taipei10087 Taiwan

Confocal microscopy is a standard modality for volumetric imaging of biological samples due to its high spatial resolution and signal-to-noise ratio (SNR). However, the slow point-by-point scanning process limits its image acquisition speed. Multifocal illumination allows for faster acquisition but compromises spatial resolution. Here, we introduce a deep learning approach for multifocal confocal microscopy that achieves faster acquisition while preserving high resolution. The proposed model is based on image-to-image translation, implemented using modified U-Net, ResU-Net, and Attention U-Net architectures. The model is trained and tested on paired experimental datasets, with conventional confocal images as groundtruth and multifocal confocal images as input from various biological samples. The modified Attention U-Net significantly improves image quality and retains structural details, with higher peak SNR (32.83 dB) and structural similarity index measure (0.935) values. Additionally, spatial frequency analysis and Fourier ring correlation confirm that the Attention U-Net outperforms other models in preserving both low-frequency (>0.92 accuracy) and high-frequency information (0.90 vs. 0.83 for U-Net). Performance metrics demonstrate that our models match the quality of traditional confocal imaging, increasing imaging speed and addressing the trade-off between speed and resolution in multifocal confocal microscopy. These findings underscore the potential of combining deep learning with various confocal imaging applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Fluorescence microscopy

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Enzymes immobilized in wood-derived cellulose scaffold for constructing a novel modular bioreactor

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Green Chemical engineering 2023年第1期4卷 39-48页

作者： Zhihong Zhang Mengchen Jin Guiru Chen Jiandu Lei Luying Wang Jun Ge Beijing Key Laboratory of Lignocellulosic Chemistry Beijing Forestry UniversityBeijing100083China Key Lab for Industrial Biocatalysis Ministry of EducationDepartment of Chemical EngineeringTsinghua UniversityBeijing100084China MOE Engineering Research Center of Forestry Biomass Materials and Bioenergy Beijing Forestry UniversityBeijing100083China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen518107China

Modular bioreactors can provide a flexible platform for constructing complex multi-step pathways,which may be a solution for maximizing reactions and overcoming the complexity of multi-enzyme ***,we selected wood-derived cellulose scaffold as a support for enzyme immobilization and constructed the modular *** scaffold was prepared after removing lignin from wood,followed by citric acid functionalization and the addition of glutaraldehyde finally allowed the cross-linking of *** enzymes,horseradish peroxidase(HRP),glucose oxidase(GOD),and catalase(CAT),were separately immobilized,resulting in the immobilized enzyme amount to over 40 mg/*** introduction of carboxyl groups from citric acid facilitated the rapid enzyme adsorption on the support surface and immobilized enzymes possess~65%expressed *** bioreactors were constructed by using the immobilized *** the immobilized HRP module,reactor showed desired catalytic performance with the phenol degradation rate of>90%.Also,a pH regulation can occur in the bioreactors for preserving enzyme activities and neutralizing acid *** the GOD/CAT modular bioreactor,the cascade reaction with adjusting pH values can achieve a 95%yield of sodium gluconate and exhibit a favorable reusability of 5 operation cycles.

关键词： Wood Immobilized enzyme Citric acid Modular bioreactor Cascade reaction

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Dual Dynamic Consistency Regularization for Semi-Supervised Domain Adaptation

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IEEE Access 2024年 12卷 36267-36279页

作者： Ngo, Ba Hung Lam, Ba Thinh Nguyen, Thanh Huy Dinh, Quang Vinh Choi, Tae Jong Chonnam National University Graduate School of Data Science Gwangju61186 Korea Republic of University of Science Faculty of Information Technology Ho Chi Minh City700000 Viet Nam National Cheng Kung University Department of Biomedical Engineering Tainan70101 Taiwan Vietnamese-German University School of Electrical Engineering and Computer Science Ho Chi Minh City72000 Viet Nam

The Vision Transformer (ViT) model serves as a powerful model to capture and comprehend global information, particularly when trained on extensive datasets. Conversely, the Convolutional Neural Network (CNN) model is beneficial to training with small datasets for retaining essential local information. Inspired by these properties of ViT and CNN models, we introduce a hybrid framework that smoothly increases the cross-domain generalization in Semi-supervised Domain Adaptation (SSDA). To achieve this goal, we first train the ViT model on abundant labeled source data, while the CNN model is trained on a few labeled target samples. Then, these models dynamically exchange their knowledge for potential generalization to unlabeled target data via the proposed method, named Dual Dynamic Consistency Regularization (D2CR). Specifically, the ViT model provides its pseudo labels to update the global perspective for the CNN model. Similarly, the CNN model offers pseudo labels to complement the local perspective for the ViT model. The previous methods use a fixed threshold algorithm for the pseudo-labeling process. However, we utilize the dynamic threshold strategy to create pseudo labels for the bi-directional consistency regularization learning between the ViT and CNN models. We verify our approach across several SSDA benchmark datasets. The outstanding experimental results provide strong evidence of the effectiveness and superiority of our approach over previous state-of-the-art SSDA methods. © 2013 IEEE.

关键词： Neural network models

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Self-supervised neural network for phase retrieval in QDPC microscopy

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Optics Express 2023年第12期31卷 19897-19908页

作者： Chen, Ying-Ju Vyas, Sunil Huang, Hsuan-Ming Luo, Yuan Institute of Medical Device and Imaging National Taiwan University Taipei10051 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10051 Taiwan YongLin Institute of Health National Taiwan University Taipei10051 Taiwan Program for Precision Health and Intelligent Medicine Graduate School of Advanced Technology National Taiwan University Taipei10051 Taiwan

Quantitative differential phase contrast (QDPC) microscope plays an important role in biomedical research since it can provide high-resolution images and quantitative phase information for thin transparent objects without staining. With weak phase assumption, the retrieval of phase information in QDPC can be treated as a linearly inverse problem which can be solved by Tikhonov regularization. However, the weak phase assumption is limited to thin objects, and tuning the regularization parameter manually is inconvenient. A self-supervised learning method based on deep image prior (DIP) is proposed to retrieve phase information from intensity measurements. The DIP model that takes intensity measurements as input is trained to output phase image. To achieve this goal, a physical layer that synthesizes the intensity measurements from the predicted phase is used. By minimizing the difference between the measured and predicted intensities, the trained DIP model is expected to reconstruct the phase image from its intensity measurements. To evaluate the performance of the proposed method, we conducted two phantom studies and reconstructed the micro-lens array and standard phase targets with different phase values. In the experimental results, the deviation of the reconstructed phase values obtained from the proposed method was less than 10% of the theoretical values. Our results show the feasibility of the proposed methods to predict quantitative phase with high accuracy, and no use of ground truth phase. © 2023 Optica Publishing Group.

关键词： Inverse problems

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In Vivo Research of Time-Lapse Changes on Surgical Sutures by OCT Signal Analysis

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Optics and Photonics Journal 2025年第1期15卷 1-8页

作者： Fengcheng Wei Hinata Nakakubo Nene Amishiro Masato Ohmi Biomedical Optics Laboratory Department of Medical Physics and Engineering Division of Health Sciences Graduate School of Medicine Osaka University Osaka Japan

Currently, animal and clinical research on biomaterials, such as surgical sutures, are mainly performed by removing them from the experiment targets and observing them by microscopy. However, traditional microscopy is not able to observe the internal structure, and there is a risk of sacrificing animals to remove the suture and damaging the materials. Therefore, we introduced optical coherence tomography (OCT) to observe and evaluate four different kinds of surgical sutures in vivo (monofilament absorbable and nonabsorbable sutures and braided absorbable and nonabsorbable sutures). As a result, while the monofilament nonabsorbable sutures showed almost no change over time, the absorbable sutures had color fading and it was also confirmed that the internal structure became chaotic due to decomposition, which improved the OCT signal intensity. For the braided sutures, both absorbable and nonabsorbable, we found that the reflection signal improved from week 0 because blood got among the filaments of sutures and dried during recovery which increased OCT signal from week 0 to week 1. We also confirmed that the braided sutures untwisted over time. All four kinds of sutures were pulled due to the movement of rats during recovery. It is expected that OCT technology will be of great help in in vivo experiments on biomaterials such as sutures.

关键词： Optical Coherence Tomography Surgical Suture biomedical PLA/PCL PVDF PGA PEs In Vivo Animal Experiment

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Dual channel CW nnU-Net for 3D PET-CT Lesion Segmentation in 2024 autoPET III Challenge

arXiv

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arXiv 2024年

作者： Wang, Ching-Wei Su, Ting-Sheng Liu, Keng-Wei Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan

PET/CT is extensively used in imaging malignant tumors because it highlights areas of increased glucose metabolism, indicative of cancerous activity. Accurate 3D lesion segmentation in PET/CT imaging is essential for effective oncological diagnostics and treatment planning. In this study, we developed an advanced 3D residual U-Net model for the Automated Lesion Segmentation in Whole-Body PET/CT - Multitracer Multicenter Generalization (autoPET III) Challenge, which will be held jointly with 2024 Medical Image Computing and Computer Assisted Intervention (MICCAI) conference at Marrakesh, Morocco. Proposed model incorporates a novel sample attention boosting technique to enhance segmentation performance by adjusting the contribution of challenging cases during training, improving generalization across FDG and PSMA tracers. The proposed model outperformed the challenge baseline model in the preliminary test set on the Grand Challenge platform, and our team is currently ranking in the 2nd place among 497 participants worldwide from 53 countries (accessed date: 2024/9/4), with Dice score of 0.8700, False Negative Volume of 19.3969 and False Positive Volume of 1.0857. GitHub repository is available at https://***/cwwang1979/CWnnU-Net-for-PET-CT © 2024, CC BY.

关键词： Image 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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Voltage-modulated surface plasmon resonance biosensors integrated with gold nanohole arrays

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biomedical Optics Express 2023年第1期14卷 182-193页

作者： Ma, Syu-Cing Gupta, Rohit Ondevilla, Neil Adrian P. Barman, Kuntal Lee, Liang-Yun Chang, Hsien-Chang Huang, Jian-Jang Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei Taiwan Department of Biomedical Engineering National Cheng Kung University Tainan Taiwan Medical Device Innovation Center National Cheng Kung University Tainan Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

Surface plasmon resonance (SPR) has emerged as one of the most efficient and attractive techniques for optical sensors in biological applications. The traditional approach of an EC (electrochemical)-SPR biosensor to generate SPR is by adopting a prism underneath the sensing substrate, and an angular scan is performed to characterize the reflectivity of target analytes. In this paper, we designed and investigated a novel optical biosensor based on a hybrid plasmonic and electrochemical phenomenon. The SPR was generated from a thin layer of gold nanohole array on a glass substrate. Using C-Reactive Protein (CRP) as the target analyte, we tested our device for different concentrations and observed the optical response under various voltage bias conditions. We observed that SPR response is concentration-dependent and can be modulated by varying DC voltages or AC bias frequencies. For CRP concentrations ranging from 1 to 1000 µg/mL, at the applied voltage of -600 mV, we obtained a limit of detection for this device of 16.5 ng/mL at the resonance peak wavelength of 690 nm. The phenomenon is due to spatial re-distribution of electron concentration at the metal-solution interface. The results suggest that CRP concentration can be determined from the SPR peak wavelength shift by scanning the voltages. The proposed new sensor structure is permissible for various future optoelectronic integration for plasmonic and electrochemical sensing. © 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Surface plasmon resonance

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PGLYRP1 protein as a novel mediator of cellular dialogue in neuroinflammation

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Neural Regeneration Research 2025年第7期20卷 1993-1994页

作者： Anup Bhusal Won-Ha Lee Kyoungho Suk Department of Pharmacology School of MedicineKyungpook National UniversityDaeguRepublic of Korea BK21 Plus KNU Biomedical Convergence Program Department of Biomedical ScienceSchool of MedicineKyungpook National UniversityDaeguRepublic of Korea School of Life Sciences BK21 plus KNU Creative BioResearch GroupKyungpook National UniversityDaeguRepublic of Korea Brain Science and Engineering Institute Kyungpook National UniversityDaeguRepublic of Korea

Neuroinflammation has been identified as a crucial element in several neurological disorders. Glial cells play a critical role in directing neuroinflammation, both in deleterious and beneficial ways.

关键词： inflammation considerably

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