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NIR-Responsive Methotrexate-Modified Iron Selenide Nanorods for Synergistic Magnetic Hyperthermic, photothermal, and Chemodynamic Therapy

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ACS Applied Materials and Interfaces 2024年第20期16卷 25622-25636页

作者： Thirumurugan, Senthilkumar Muthiah, Kayalvizhi Samuvel Lin, Yu-Chien dhawan, Udesh Liu, Wai-Ching Wang, An-Ni Liu, Xinke Hsiao, Michael Tseng, Ching-Li Chung, Ren-Jei No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom Faculty of Science and Technology Technological and Higher Education Institute of Hong Kong Hong Kong New Territories999077 Hong Kong Scrona AG Grubenstrasse 9 Zürich8045 Switzerland College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Genomics Research Center Academia Sinica Taipei115 Taiwan Department and Graduate Institute of Veterinary Medicine School of Veterinary Medicine National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Taipei10608 Taiwan

Breast cancer is a malignant tumor with a high mortality rate among women. Therefore, it is necessary to develop novel therapies to effectively treat this disease. In this study, iron selenide nanorods (FeSe2 NRs) were designed for use in magnetic hyperthermic, photothermal, and chemodynamic therapy (MHT/PTT/CdT) for breast cancer. To illustrate their efficacy, FeSe2 NRs were modified with the chemotherapeutic agent methotrexate (MTX). MTX-modified FeSe2 (FeSe2-MTX) exhibited excellent controlled drug release properties. Fe2+ released from FeSe2 NRs induced the release of •OH from H2O2 via a Fenton/Fenton-like reaction, enhancing the efficacy of CdT. Under alternating magnetic field (AMF) stimulation and 808 nm laser irradiation, FeSe2-MTX exerted potent hyperthermic and photothermal effects by suppressing tumor growth in a breast cancer nude mouse model. In addition, FeSe2 NRs can be used for magnetic resonance imaging in vivo by incorporating their superparamagnetic characteristics into a single nanomaterial. Overall, we presented a novel technique for the precise delivery of functional nanosystems to tumors that can enhance the efficacy of breast cancer treatment. © 2024 The Authors. Published by American Chemical Society

关键词： Magnetic resonance imaging

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A microfluidic chip for multiple single-cell interaction analysis 22

A microfluidic chip for multiple single-cell interaction ana...

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22nd international Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2018

作者： He, Cheng-Kun Chen, Chihchen Hsu, Chia-Hsien Ph.D. Program in Tissue Engineering and Regenerative Medicine National Chung Hsing University Taichung Taiwan Institute of NanoEngineering and MicroSystems National Tsing Hua University Hsinchu Taiwan Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes Miaoli Taiwan

ISBN: (纸本)9781510897571

The traditional co-culture systems can only be used to describe the population signal, but unable to track individual cells behavior. Our chip demonstrates the ability to high-efficiently capture more than two types of single cells in a large chamber and provide a sufficient culture space useful for studying multiple single cell type interactions. Copyright © (2018) by Chemical and Biological Microsystems Society. All rights reserved.

关键词： Lab-on-a-chip

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Transdermally administered nanozymes-infused F127/methylcellulose hydrogel for osteoarthritis relief via immunomodulatory pathways

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international journal of biological macromolecules 2025年 314卷 144114页

作者： Chih-Kuang Chen Hui-Wen Chiu Hieu Trung Nguyen Hsien-Tsung Lu Andrew E-Y Chuang Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan Department of Physical Medicine and Rehabilitation Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan School of Medicine Chang Gung University Taoyuan Taiwan. Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Department of Orthopedics and Trauma Faculty of Medicine University of Medicine and Pharmacy at Ho Chi Minh City Ho Chi Minh City 700000 Viet Nam. Department of Orthopedics School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan Department of Orthopedic Taipei Medical University Hospital Taipei City 11031 Taiwan. Electronic address: lu7788@tmu.edu.tw. Cell Physiology and Molecular Image Research Center Taipei Medical University-Wan Fang Hospital Taipei 11696 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University New Taipei City 235603 Taiwan. Electronic address: eychuang@tmu.edu.tw.

Osteoarthritis (OA) is a debilitating condition characterized by chronic inflammation, oxidative stress, hypoxia, angiogenesis-driven pain, and cartilage degradation, thus presenting significant therapeutic challenges. Herein, we introduce a wearable percutaneous hydrogel (Pluronic F127/methylcellulose) encapsulation platform, designed to address the multifaceted pathology of OA through a synergistic integration of multifunctional components. This nanomedicine-hydrogel system incorporates platelet-derived extracellular vesicles (pEVs) for inflammation delivery, phototherapeutic molybdenum disulfide (MoS2), capsaicin (CAP) and diferuloylmethane (dIF) for potent anti-inflammatory and antioxidative effects and hydrogen-bonded organic frameworks (HOFs) to enhance drug encapsulation and conductivity. Experimental findings demonstrated the pEV/MoS2/dIF/CAP NZHOF@F127/MC's ability to mitigate inflammation by promoting macrophage polarization from the M1 to the M2 phenotype, alleviate oxidative stress, inhibit angiogenesis, and modulate hypoxic microenvironments through the percutaneous phototherapeutic pEV/MoS2/dIF/CAP NZ-HOF@F127/MC. In vivo studies in a rat model of OA revealed substantial reductions in joint inflammation, enhanced cartilage regeneration, and improved mobility following near-infrared (NIR)-triggered phototherapy. The pEV/MoS2/dIF/CAP NZ-HOF@F127/MC's multifaceted mechanisms, including precise drug delivery, controlled release, and on-demand photo-responsiveness, underscore its transformative potential for OA management. These findings present a promising therapeutic strategy for OA, addressing inflammation, oxidative stress, and joint lesion mitigation, with strong potential for clinical translation.

关键词： Anti-inflammation Immunomodulation Modulation of hypoxic microenvironment Osteoarthritis alleviation Percutaneous phototherapeutic pEV/MoS2/dIF/CAP NZ-HOF@F127/MC

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3d Brain Tumor Segmentation in Multimodal MRI Images

3D Brain Tumor Segmentation in Multimodal MRI Images

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IEEE international Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Nisar Ahmad Yao-Tien Chen International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

In brain tumor research, the use of machine learning based methods using MRI data to locate brain tumors accurately has significantly increased and new techniques are proposed to facilitate the medical experts. There is still room for improvement as tumors have complex anatomy which requires efforts to explore further and propose new deep learning based solutions. In this research, we propose 3d UNet based multimodal brain tumor segmentation for Non Enhancing Tumor (NET), Peritumoral Edema (PE), and Enhancing Tumor (ET). data preprocessing and augmentation techniques are employed to optimise the model's performance. The dataset used in this study to train, validate, and test the model performance is the BraTS 2020 dataset. The model achieved improved accuracy and IoU after implementing the mentioned techniques. Results before and after data augmentation demonstrate a significant enhancement in model performance. The model achieved an improved mIoU of 0.77 and accuracies of 98.21% and 99.36% for actual data and augmented data for three brain tumor classes, i.e., NET, PE, and ET. Our model performed multiclass brain tumor segmentation with high accuracies, and we aim to enhance this study to propose a valuable medical assistance model.

关键词： Solid modeling Image segmentation Three-dimensional displays Accuracy Magnetic resonance imaging Brain modeling data augmentation

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Investigation of Short-Circuit Current density in Non-Fullerene-Based Ternary Organic Solar Cells by Incorporating Machine Learning Algorithms with Effective descriptors

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Solar RRL 2025年

作者： Lee, Min-Hsuan Chen, Ying-Chun Chang, Yi-Ming Hou, Bo Ph.D. Program in Biomedical Artificial Intelligence National Tsing Hua University Hsinchu Taiwan Institute of Environmental and Occupational Health Sciences School of Medicine National Yang-Ming Chiao Tung University Taipei Taiwan Institute of Environmental Engineering National Yang-Ming Chiao Tung University Hsinchu Taiwan Department of Mechanical Engineering National Taiwan University of Science and Technology Taipei Taiwan Raynergy Tek Incorporation Hsinchu Taiwan School of Physics and Astronomy Cardiff University Cardiff United Kingdom

Non-fullerene acceptor (NFA)-based ternary organic solar cells (OSCs) are emerging as promising devices for converting sunlight into electricity, contributing to environmental solutions. However, selecting the third component remains a significant challenge, as it plays a critical role in achieving high short-circuit current density (Jsc) in NFA-based ternary OSCs (comprising donors, acceptors, and the third component). Traditional trial-and-error experimental methods face substantial limitations, including high energy consumption, cost, and time demands, which may not be sufficient for investigating the quantitative relationships between material properties and Jsc in ternary OSCs. In this study, we examine the effects of the highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO–LUMO) energy gap (ΔHOMO and ΔLUMO) between different organic materials, considering these as effective molecular descriptors, on the primary photovoltaic parameter (Jsc) in NFA-based ternary OSCs. The eXtreme Gradient Boosting (XGBoost) algorithm yields reasonable predictions, with an R2 value of 0.76. Additionally, three NFA-based ternary OSCs are fabricated and characterized experimentally to validate the predictions made by the proposed model. Using three different NFA-based ternary OSCs as inputs, the model demonstrates good predictive accuracy for Jsc values. The proposed interpretable model and effective molecular descriptors offer a practical machine-learning approach for accelerating the development of NFA-based ternary OSCs with targeted Jsc values and can also be extended to other organic electronic applications. © 2025 Wiley-VCH GmbH.

关键词： Learning algorithms

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Enhanced deep Learning Model Performance in 3d Multimodal Brain Tumor Segmentation with Gabor Filter

Enhanced Deep Learning Model Performance in 3D Multimodal Br...

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international Conference on Applied System Innovation (ICASI)

作者： Nisar Ahmad Yao-Tien Chen International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

Medical image segmentation plays a crucial role in identifying and analyzing anatomical structures in medical images. This requires an accurate medical segmentation tool to delineate and quantitatively analyze the target regions, diagnose any abnormality, and assist in treatment planning. deep learning approaches have emerged as a promising solution for automating medical segmentation. However, challenges arise when dealing with the complex shapes and spatial variations of some target regions, especially in 3d MRI scans. To deal with such transformations, specific techniques are required to properly analyze and preprocess the dataset and perform image filtering to provide better features for improved prediction performance of deep learning architectures. This study focuses on improving brain tumor segmentation in multimodal 3d MRI images. We observed significant improvements in multimodal brain tumor segmentation results (accuracy, IoU, and mIoU) using an optimized 3d Gabor filter, which helps extract meaningful features. Multichannel input images were preprocessed to remove noise and select an appropriate resolution to reduce computational complexity. An improvement in mean Intersection over Union (mIoU) from 0.714 to 0.804 and accuracy from 0.982 to 0.991 were achieved, which shows a major improvement. This work contributes to the field of medical image segmentation by offering an improved and efficient approach for brain tumor analysis in 3d MRI scans, potentially aiding in diagnosis and treatment planning.

关键词： deep learning Image segmentation Solid modeling Three-dimensional displays Magnetic resonance imaging Feature extraction Planning

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UNet-based Automatic Multicalss Brain Tissue Segmentation

UNet-based Automatic Multicalss Brain Tissue Segmentation

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IEEE international Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Nisar Ahmad Yao-Tien Chen International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City Taiwan

In brain research, brain tissue segmentation techniques have offered vast aid and possibilities for quantitative analysis of the brain to detect brain tumor and other brain issues. In this paper, UNet-based multiclass brain tissue segmentation is presented. To achieve the best performance of the model, data augmentation techniques are applied. The training, validation and testing of the model is performed on the BrainWeb dataset. The model has achieved improved accuracy and IoU after data augmentation. Both pre and post data augmentation results are presented which show clear improvement in model performance after data augmentation. The achieved IoU for white matter, gray matter and cerebrospinal fluid are 0.84, 0.95 and 0.92, respectively. Our model accurately performed the multiclass brain tissue segmentation and this study proposes a valuable medical aid model.

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Advanced ZnFe₂O₄@f-CNF electrode: A robust electrochemical sensor for Tert-butyl hydroquinone detection in food and edible oil

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Food Chemistry 2025年 486卷 144648页

作者： Yemmi, Rajeshwari Swamy, B.E. Kumara Manjunath, Kumbar Mudakappa Yusuf, Kareem Aljuwayid, Ahmed M. Govindasamy, Mani 577451 India Division of Plant Breeding and Genetics Central Coffee Research Institute Karnataka Chikkamagaluru577117 India Department of Chemistry College of Science King Saud University Riyadh11451 Saudi Arabia International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City243303 Taiwan Research Center for Intelligence Medical Devices Ming Chi University of Technology New Taipei City243303 Taiwan Department of Chemistry Korea University Seoul Seongbuk-gu Korea Republic of

Fabrication of a binary electrocatalyst is expounded in this study, which is based on a biocompatible ZnFe2O4 nanoparticles that is adorned onto the functionalized carbon nanofiber (f-CNF) through a straightforward ultrasonication technique. This electrocatalyst is applied for the reliable quantification of the food additive Tert-Butyl Hydroquinone (TBHQ) from various food samples and products. The electrochemical performance of the ZnFe2O4@f-CNF composite is investigated using cyclic voltammetry and electrochemical impedance spectroscopy analysis. The structural features of the composite, characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy which reveals its crystalline and porous attributes. Then electrochemical characteristics of the ZnFe2O4@f-CNF composite for TBHQ detection is evaluated employing cyclic voltammetry and differential pulse voltammetry methodologies. Notably, this composite demonstrates a remarkable low detection limit (LOd) of 0.026 μM with a good linear detection range, accompanied by a favorable sensitivity towards TBHQ. Lastly, the developed sensor system manifests a substantial recovery range for real sample analysis, suggesting its potential as a viable alternative to existing diagnostic tools for TBHQ detection. © 2025 Elsevier Ltd

关键词： Cyclic voltammetry

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Early Intervention Mechanism for Preventing Electrical Shocks during Construction Projects: Portable Electrical Equipment 3

Early Intervention Mechanism for Preventing Electrical Shock...

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3rd international Conference on Electrical engineering and Green Energy, CEEGE 2020

作者： Shiau, Yau-Ren Lo, Fang-Yi Ko, Po-Cheng Department of Industrial Engineering and Systems Management Feng Chia University Taichung40724 Taiwan Department of International Business Feng Chia University Taichung40724 Taiwan Ph.D. Program of Business Feng Chia University Taichung40724 Taiwan

To prevent electrical shock accidents in construction sites, the present researchers used portable electrical equipment as an example to plan a preconstruction early intervention mechanism that can be used to conduct various inspections of portable electrical devices. This study used narrative text analysis for data collection and compilation. The researchers analyzed 41 real electrocution death cases involving portable electric equipment as the electrocution medium in the Taiwanese construction industry and identified hazard factors that cause electrocution from the case summaries. Then, the IdEF3 was used to integrate and construct a model for the portable electrical equipment inspection flowchart of the early intervention mechanism as a safety inspection system to prevent electrocution in construction engineering units. This study revealed hazard factors and management omissions related to electrocutions caused by portable electrical equipment. To protect workers and strengthen the safety of the construction site, this study proposed of an electric shock prevention early intervention mechanism for portable electric equipment in construction projects. Various inspections should be conducted before equipment is brought on site for construction operations to ensure the safety of electrical equipment and reduce electrocution risks. This study also established a visualization mechanism for the visual qualification label of portable electrical equipment. This mechanism is conducive to strengthening safety management. © The Authors, published by EdP Sciences, 2020.

关键词： Construction industry

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Using electroencephalography signals to explore the influence of Zentangle on meditation and mindfulness 9

Using electroencephalography signals to explore the influenc...

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9th international Conference on Applied System Innovation, ICASI 2023

作者： Usman, Muhammad Lin, Chun-Ling Ming Chi University of Technology International Ph.D Program in Innovative Technology of Biomedical Engineering and Medical Devices New Taipei City Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei City Taiwan

ISBN: (纸本)9798350398380

Fifteen novices completed a Zentangle task while their brain activity was measured with electroencephalography (EEG) and their concentration emotional state, stress, and anxiety levels were evaluated with questionnaires. The study found increased activity in theta, alpha, beta, and gamma ranges associated with relaxation, focus, and mental activity. Participants reported improved concentration, emotional state, and reduced stress and anxiety levels after completing the task, suggesting the potential of Zentangle to enhance cognitive and emotional well-being. © 2023 IEEE.

关键词： Electroencephalography

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