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Preclinical Assessment of Enhanced Chemodynamic Therapy by an FeMnOx-Based Nanocarrier: Tumor-Microenvironment-Mediated Fenton Reaction and ROS-Induced Chemotherapeutic for Boosted Antitumor Activity

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ACS Applied Materials and Interfaces 2023年第48期15卷 55258-55275页

作者： dirersa, Worku Batu Kan, Tzu-Chun Getachew, Girum Wibrianto, Aswandi Ochirbat, Sonjid Rasal, Akash Chang, Jungshan Chang, Jia-Yaw Department of Chemical Engineering National Taiwan University of Science and Technology Taiwan Taipei106335 Taiwan Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei11031 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan International Ph.D. Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan

In recent studies, iron-containing Fenton nanocatalysts have demonstrated significant promise for clinical use due to their effective antitumor activity and low cytotoxicity. A new approach was reported in this work utilizing cation exchange synthesis to fabricate FeMnOx nanoparticles (NPs) that boost Fenton reactions and responses to the tumor microenvironment (TME) for chemodynamic therapy (CdT) and chemotherapy (CT). Within the TME, the redox metal pair of Fe2+/Mn2+ helps break down endogenous hydrogen peroxide (H2O2) into very harmful hydroxyl radicals (•OH) while simultaneously deactivating glutathione (GSH) to boost CdT performance. To further enhance the therapeutic potential, FeMnOx NPs were encapsulated with thioketal-linked camptothecin (CPT-TK-COOH), a reactive oxygen species (ROS)-responsive prodrug, achieving a high CPT-loading capacity of up to 51.1%. Upon ROS generation through the Fenton reaction, the prodrug TK linkage was disrupted, releasing 80% of the CPT payload within 48 h. Notably, FeMnOx@CPT exhibited excellent dual-modal imaging capabilities, enabling magnetic resonance and fluorescence imaging for image-guided therapy. In vitro studies showed the cytocompatibility of FeMnOx NPs using MdA-Mb-231 and 4T1 cells, but in the presence of H2O2, they induced significant cytotoxicity, resulting in 80% cell death through CdT and CT effects. Upon intravenous administration, FeMnOx@CPT displayed remarkable tumor accumulation, which enhanced tumor suppression in xenografts through improved CdT and CT effects. Moreover, no significant adverse effects were observed in the FeMnOx NP-treated animals. In the current study, the FeMnOx@CPT anticancer platform, with its boosted •OH-producing capability and ROS-cleavable drug release, has been validated utilizing in vitro and animal studies, suggesting its capacity as a viable strategy for clinical trials. © 2023 American Chemical Society.

关键词： Chemotherapy

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engineering H2O2 Self-Supplying Platform for Xdynamic Therapies via Ru-Cu Peroxide Nanocarrier: Tumor Microenvironment-Mediated Synergistic Therapy

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ACS Applied Materials and Interfaces 2024年第19期16卷 24172-24190页

作者： dirersa, Worku Batu Kan, Tzu-Chun Chang, Jungshan Getachew, Girum Ochirbat, Sonjid Kizhepat, Shamsa Wibrianto, Aswandi Rasal, Akash Chen, Hung-An Ghule, Anil Vithal Chou, Tzung-Han Chang, Jia-Yaw Department of Chemical Engineering National Taiwan University of Science and Technology Taipei106335 Taiwan Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei11031 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan International Ph.D. Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Green Nanotechnology Laboratory Department of Chemistry Shivaji University Kolhapur416004 India Department of Chemical and Materials Engineering National Yunlin University of Science and Technology Yunlin64002 Taiwan

Of the most common, hypoxia, overexpressed glutathione (GSH), and insufficient H2O2 concentration in the tumor microenvironment (TME) are the main barriers to the advancment of reactive oxygen species (ROS) mediated Xdynamic therapies (X = photo, chemodynamic, chemo). Maximizing Fenton catalytic efficiency is crucial in chemodynamic therapy (CdT), yet endogenous H2O2 levels are not sufficient to attain better anticancer efficacy. Specifically, there is a need to amplify Fenton reactivity within tumors, leveraging the unique attributes of the TME. Herein, for the first time, we design RuxCu1-xO2-Ce6/CPT (RCpCCPT) anticancer nanoagent for TME-mediated synergistic therapy based on heterogeneous Ru-Cu peroxide nanodots (RuxCu1-xO2 Nds) and chlorine e6 (Ce6), loaded with ROS-responsive thioketal (TK) linked-camptothecin (CPT). The Ru-Cu peroxide Nds (RCp Nds, x = 0.50) possess the highest oxygen vacancy (OV) density, which grants them the potential to form massive Lewis’s acid sites for peroxide adsorption, while the dispersibility and targetability of the Nds were improved via surface modification using hyaluronic acid (HA). In TME, RCpCCPT degrades, releasing H2O2, Ru2+/3+, and Cu+/2+ ions, which cooperatively facilitate hydroxyl radical (•OH) formation and deactivate antioxidant GSH enzymes through a cocatalytic loop, resulting in excellent tumor therapeutic efficacy. Furthermore, when combined with laser treatment, RCpCCPT produces singlet oxygen (1O2) for PdT, which induces cell apoptosis at tumor sites. Following ROS generation, the TK linkage is disrupted, releasing up to 92% of the CPT within 48 h. In vitro investigations showed that laser-treated RCpCCPT caused 81.5% cell death from PdT/CdT and chemotherapy (CT). RCpCCPT in cancer cells produces red-blue emission in images of cells taking them in, which allows for fluorescence image-guided Xdynamic treatment. The overall results show that RCp Nds and RCpCCPT are more biocompatible and have excellent Xdynamic the

关键词： Oxidation

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Macroscopic discolorization in Quantum dot Color Converters for Microdisplay Applications

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ACS Applied Nano Materials 2024年第7期7卷 8258-8268页

作者： Lin, Chen-Te Chen, Hsueh-Shih Ph.D. Program in Prospective Functional Materials Industry College of Engineering National Tsing Hua University Hsinchu30013 Taiwan Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu30013 Taiwan

Quantum dot color converters (QdCCs) currently have the unsolved problems of photostability and discolorization in appearance after long-term operation in microdisplays. Instead of polymer-to-carbon conversion and/or impurity precipitation, the macroscopic bright-yellow-to-dark-brown discolorization is determined by microscopic interfacial chemical reactions of the Qd-ligand-polymer system. The phenomenon has been confirmed to be related to multiple factors, including chemical transformation of the Qd shell and partial degradation of the polymer, resulting in increased optical reflectance and reduced photoluminescence (PL) intensity in QdCCs. Our finding suggests that the photoexcitation of Qds in the polymer matrix should lead to detached surface ligands along with photocatalytic reactions, oxidizing the Qd shell together with degrading the polymer chains. © 2024 The Authors. Published by American Chemical Society

关键词： Color

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Overcoming the Blood-Brain Tumor Barrier with docetaxel-Loaded Mesoporous Silica Nanoparticles for Treatment of Temozolomide-Resistant Glioblastoma

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ACS Applied Materials and Interfaces 2024年第17期16卷 21722-21735页

作者： Hsu, Tsung-I Chen, Yi-Ping Zhang, Rong-Lin Chen, Zih-An Wu, Cheng-Hsun Chang, Wen-Chang Mou, Chung-Yuan Chan, Hardy Wai-Hong Wu, Si-Han Ph.D. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University and National Health Research Institutes Taipei110 Taiwan International Master Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei110 Taiwan Graduate Institute of Nanomedicine and Medical Engineering Taipei Medical University Taipei110 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei110 Taiwan Nano Targeting & Therapy Biopharma Inc. Taipei110 Taiwan Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei110 Taiwan Department of Chemistry National Taiwan University Taipei106 Taiwan

While temozolomide (TMZ) has been a cornerstone in the treatment of newly diagnosed glioblastoma (GBM), a significant challenge has been the emergence of resistance to TMZ, which compromises its clinical benefits. Additionally, the nonspecificity of TMZ can lead to detrimental side effects. Although TMZ is capable of penetrating the blood-brain barrier (BBB), our research addresses the need for targeted therapy to circumvent resistance mechanisms and reduce off-target effects. This study introduces the use of PEGylated mesoporous silica nanoparticles (MSN) with octyl group modifications (C8-MSN) as a nanocarrier system for the delivery of docetaxel (dTX), providing a novel approach for treating TMZ-resistant GBM. Our findings reveal that C8-MSN is biocompatible in vitro, and dTX@C8-MSN shows no hemolytic activity at therapeutic concentrations, maintaining efficacy against GBM cells. Crucially, in vivo imaging demonstrates preferential accumulation of C8-MSN within the tumor region, suggesting enhanced permeability across the blood-brain tumor barrier (BBTB). When administered to orthotopic glioma mouse models, dTX@C8-MSN notably prolongs survival by over 50%, significantly reduces tumor volume, and decreases side effects compared to free dTX, indicating a targeted and effective approach to treatment. The apoptotic pathways activated by dTX@C8-MSN, evidenced by the increased levels of cleaved caspase-3 and PARP, point to a potent therapeutic mechanism. Collectively, the results advocate dTX@C8-MSN as a promising candidate for targeted therapy in TMZ-resistant GBM, optimizing drug delivery and bioavailability to overcome current therapeutic limitations. © 2024 The Authors. Published by American Chemical Society.

关键词： Tumors

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A High-step-down Converter with Negative Output Voltage 11

A High-step-down Converter with Negative Output Voltage

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11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Yau, Yeu-Torng Luu, Thanh-phu. National Chin-Yi University of Technology Ph.D. Program Ptoeecs Taichung Taiwan National Chin-Yuuuuuuui University of Technology Department of Electrical Engineering Taichung Taiwan

ISBN: (纸本)9788957083505

This paper proposes a new high step-down converter with negative voltage output, which has the following advantages: (1) Compared to conventional buck-boost or SEPIC converters, the proposed converter operates with zero voltage turn-on function. (2) The voltage gain of this circuit does not contain non-linear components, and the control is simple and can be driven by existing buck control ICs. (3) due to the dC blocking capacitor between the output and input terminals, the high voltage at the input will not pass through to the output when the converter fails to be controlled. The load is protected. Finally, a prototype is completed and the proposed method is verified to be feasible. © 2023 The Korean Institute of Power Electronics.

关键词： Buck-Boost converter

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Students Learning Performance and Engagement in a Visual programming Environment

Students Learning Performance and Engagement in a Visual Pro...

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Proceedings of the 6th International Conference on Innovative Technologies and Learning, ICITL 2023

作者： Wen, Fu-Hsiang Wu, Tienhua Hsu, Wei-Chih Ph.D. Program in Engineering Science and Technology College of Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Management Air Force Institute of Technology Kaohsiung Taiwan Department of Computer and Communication Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9783031401121

This study employed a quasi-experimental method to explore differences in students’ learning performance and engagement between visual and textual language programming environments. Specifically, this study examined how strongly engagement dimensions affect participants’ learning achievement in a Scratch experimental setting. One hundred and thirty-two undergraduate students participated. The results revealed that participants with Scratch intervention outperformed those with text-based language instructions in terms of performance and behavioral, emotional, cognitive, and agentic engagement. The findings indicated that engagement significantly predicted student academic success in a visual learning environment. This study concluded that visual programming tools such as Scratch help novices engaged and effectively learn core aspects of programming concepts. Additionally, student engagement deepens an understanding of predictions of programmers’ behaviors and achievements and mechanisms behind the effectiveness of visualization intervention. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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Recommendation of Resource Allocation decision Based on Bipartite Graph Network Structure

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IEIE Transactions on Smart Processing and Computing 2025年第1期14卷 128-139页

作者： Pei, Wen Pan, Wen-An Huang, Jui-Chan College of Management Chung Hua University Hsinchu30012 Taiwan Ph.D Program of Management Chung Hua University Hsinchu30012 Taiwan Department of Industrial Engineering and Management National Kaohsiung University of Science and Technology Kaohsiung807618 Taiwan

In resource allocation decisions in business, fully understanding customers’ needs and preferences helps to maximise benefits. As a result, in the modern business environment, the design of customized recommendation systems has gained a lot of attention. To this end, the study designs a recommendation algorithm for resource allocation decision based on improved two-part graph network structure. In this algorithm, an improved K-means clustering algorithm is introduced to deeply mine potential information. The calculation of similarity between users is also optimised to assist the target user to find the real neighbouring users. The findings demonstrate that, in comparison to the other algorithms, the resource allocation recommendation algorithm based on improved bipartite graph suggested in the study has a greater hit rate. The hit rate of the suggested algorithm can reach 32.5% when the recommendation list length is 10, which is a 21.5% improvement over the collaborative filtering algorithm. The suggested algorithm’s popularity is only 39.1, which is 69.3 less than the collaborative filtering algorithm when the suggestion list length is 10. Furthermore, the suggested algorithm for resource allocation decision-making created by the research has a greater recommendation accuracy, more personalization, and diversity, as seen by the proposed algorithm’s mean Hamming distance of 0.976. Through an improved bipartite graph network, the algorithm can fully analyze the historical preference information of users, effectively capture the complex relationship between users and products, generate personalized recommendation lists, and improve user satisfaction and purchase conversion rates. It provides an effective recommendation role for resource allocation decisions in modern business and helps to create greater economic benefits. © 2025 Institute of Electronics Engineers of Korea. All rights reserved.

关键词： Collaborative filtering

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deep Learning-Based Positioning Error Fault diagnosis of Wire Bonding Equipment and an Empirical Study for IC Packaging

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IEEE Transactions on Semiconductor Manufacturing 2023年第4期36卷 619-628页

作者： Kao, Sheng-Xiang Chien, Chen-Fu International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan Intelligent Manufacturing and Circular Economy Research Center National Tsing Hua University Artificial Intelligence for Intelligent Manufacturing Systems Research Center National Science and Technology Council Department of Industrial Engineering and Engineering Management Hsinchu300044 Taiwan

Little research has been done for artificial intelligence applications of semiconductor backend. This study aims to develop a deep learning based fault diagnosis framework as prognostics and health management (phM) solutions with a comprehensive analytics process. A linear encoder sensor is employed to measure position, while data preparation is conducted to convert position information into a signal. Then, signal processing is used to extract the features, in which high pass filter is applied to normalize the signal and emphasize the features. High-dimensional features including time domain statistical features, time-frequency domain features obtained by continuous wavelet transform (CWT), and frequency domain features converted by fast Fourier transform (FFT) are extracted to prepare the dataset. An ensemble neural network model that integrates deep neural network (dNN) and convolutional neural network (CNN) is employed to recognize the pattern and diagnose the positioning errors. The accuracy and false alarm rate are considered to support maintenance decisions. An empirical study was conducted in a world leading IC assembly and testing company for validation. The results have shown that the proposed approach can effectively detect inappropriate installation of the bond head in wire bonding equipment for predictive maintenance and cost reduction. © 1988-2012 IEEE.

关键词： Failure analysis

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determinants of customer value at department stores in Taiwan: An application of fuzzy AHP

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Journal of Intelligent and Fuzzy Systems 2023年第6期44卷 9073-9089页

作者： ding, Ji-Feng Weng, Ju-Hui Chou, Chien-Chang Department of Aviation and Maritime Transportation Management Chang Jung Christian University Tainan City Taiwan The Ph.D. Program in Business and Operations Management Chang Jung Christian University Tainan City Taiwan Department of Shipping Technology National Kaohsiung University of Science and Technology Kaohsiung Taiwan

Evaluating the factors affecting customer value in department stores will shed light on the motivations of customers when choosing department stores, which will help department stores to improve their business performance and competitiveness. This paper applies the fuzzy Analytic Hierarchy Process (AHP) method to empirically analyze the determinants of customer value at department stores in Taiwan. This study first found the major factors influencing customer value at department stores in Taiwan through a review of the literature and expert interviews, and these factors consisted of four evaluation dimensions and 20 evaluation criteria. An empirical investigation was then conducted through an AHP expert questionnaire survey. The main findings of this paper were as follows: (1) 'physical environment' was the most important evaluation dimension for customer value at department stores in Taiwan. (2) The four leading factors influencing customer value in department stores were 'roomy and comfortable space,' 'responsive customer service,' 'planning of lines of movement at counters,' and 'parking area and facilities.' This study also performed further discussion of the four evaluation criteria as a reference for department stores that wish to raise their competitiveness. © 2023 - IOS Press. All rights reserved.

关键词： Analytic hierarchy process

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Eff-SAM: SAM-based Efficient Method for Brain Tumor Segmentation in Multimodal 3d MRI Scans

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IEEE Access 2025年 13卷 90063-90087页

作者： Ahmad, Nisar Chen, Yao-Tien Ming Chi University of Technology International Ph.D. Program in Innovative Technology of Biomedical Engineering Medical Devices New Taipei City243303 Taiwan

Accurate brain tumor segmentation in MRI scans is crucial for effective diagnosis and treatment planning, as even minor segmentation errors can lead to significant clinical concerns. However, this task is challenged by the complex anatomy of the brain, variable tumor shapes, and low contrast between tumor sub-regions. Moreover, existing methods often lack generalizability across diverse segmentation tasks and imaging modalities. Large Vision Model (LVM) like the Segment Anything Model (SAM) represents a foundational advancement in tumor segmentation. While SAM has shown impressive performance on natural images, its effectiveness in medical imaging, especially brain tumor segmentation, is limited due to domain differences and indistinct boundaries in MRI scans. To address these challenges, we propose Eff-SAM, a 3d brain tumor segmentation framework that adapts SAM for medical applications through Parameter-Efficient Fine-Tuning (PEFT) technique. The framework incorporates PEFT with adapters into SAM’s encoder to fine-tune the model effectively and optimize its performance for medical imaging while maintaining computational efficiency. Additionally, a Cross-Sliced Attention (CSA) mechanism captures semantic relationships, improves tumor localization, and is introduced into the encoder. Robust data preprocessing further enhances the model’s generalization across datasets. Eff-SAM demonstrates state-of-the-art performance and outperforms benchmark methods on the BraTS 2020 and BraTS 2021 datasets. It achieves dice scores of 0.884 for Whole Tumor (WT), 0.853 for Tumor Core (TC), and 0.818 for Enhancing Tumor (ET) on the BraTS 2020 dataset, and 0.880 (WT), 0.861 (TC), and 0.821 (ET) on the BraTS 2021 dataset. This work highlights the potential of integrating vision models like SAM with lightweight, domain-specific modules to deliver accurate and efficient brain tumor segmentation offering a clinically valuable tool, especially in scenarios with limited data and complex tu

关键词： Semantic Segmentation

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