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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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Enhanced diabetic wound healing using platelet-derived extracellular vesicles and reduced graphene oxide in polymer-coordinated hydrogels

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Journal of Nanobiotechnology 2023年第1期21卷 1-17页

作者： Hao, Ping-Chien Burnouf, Thierry Chiang, Chih-Wei Jheng, Pei-Ru Szunerits, Sabine Yang, Jen-Chang Chuang, Er-Yuan 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 Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei10617 Taiwan Department of Orthopedics Taipei Medical University Hospital Taipei11031 Taiwan Univ. Lille CNRS Centrale Lille Univ. Polytechnique Hauts-de-France UMR 8520 IEMN LilleF- 59000 France Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei110-52 Taiwan Cell Physiology and Molecular Image Research Center Taipei Medical University-Wan Fang Hospital Taipei11696 Taiwan Precision Medicine and Translational Cancer Research Center Taipei Medical University Hospital Taipei11031 Taiwan

Impaired wound healing is a significant complication of diabetes. Platelet-derived extracellular vesicles (pEVs), rich in growth factors and cytokines, show promise as a powerful biotherapy to modulate cellular proliferation, angiogenesis, immunomodulation, and inflammation. For practical home-based wound therapy, however, pEVs should be incorporated into wound bandages with careful attention to delivery strategies. In this work, a gelatin-alginate hydrogel (GelAlg) loaded with reduced graphene oxide (rGO) was fabricated, and its potential as a diabetic wound dressing was investigated. The GelAlg@rGO-pEV gel exhibited excellent mechanical stability and biocompatibility in vitro, with promising macrophage polarization and reactive oxygen species (ROS)-scavenging capability. In vitro cell migration experiments were complemented by in vivo investigations using a streptozotocin-induced diabetic rat wound model. When exposed to near-infrared light at 2 W cm− 2, the GelAlg@rGO-pEV hydrogel effectively decreased the expression of inflammatory biomarkers, regulated immune response, promoted angiogenesis, and enhanced diabetic wound healing. Interestingly, the GelAlg@rGO-pEV hydrogel also increased the expression of heat shock proteins involved in cellular protective pathways. These findings suggest that the engineered GelAlg@rGO-pEV hydrogel has the potential to serve as a wound dressing that can modulate immune responses, inflammation, angiogenesis, and follicle regeneration in diabetic wounds, potentially leading to accelerated healing of chronic wounds. © 2023, BioMed Central Ltd., part of Springer Nature.

关键词： Platelets

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A motion-level-aware denoising framework for x-ray fluoroscopic images

A motion-level-aware denoising framework for x-ray fluorosco...

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Medical Imaging 2023: Physics of Medical Imaging

作者： Jo, Geonhui Jang, Minhee Jeon, Sun-Young Kim, Wonjin Choi, Jang-Hwan Department of Computer Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of

ISBN: (纸本)9781510660311

Fluoroscopy in a low-dose tube output is used to reduce the damage associated with radiation exposure. However, lowering the radiation dose inevitably increases random noise in x-ray images, resulting in poor diagnostic image quality, which requires noise reduction for accurate diagnosis. Also, in the case of non-static objects, the image is blurred due to motion. The most-used denoiser with a recursive filter (RF) preserves details well when applied to temporal data, but it is vulnerable to motion blur. Existing convolutional neural network (CNN)-based algorithms with single-frame input cannot use the temporary context, and others with multi-frame input are good for motion detection but poor for detail preservation. Therefore, we propose a motion-level-aware denoising framework to combine the results of RF- and CNN-based algorithms depending on the pixel-wise magnitude of motion to complement each other. The data we use are fluoroscopy images taken in continuous time, and we aim at many-to-one so that one frame is denoised by considering sequential frames. Also, since both RF- and CNN-based algorithms used in our architecture are many-to-one methods, they can consider spatiotemporal information. In the multi-frame input, the difference in intensity of each pixel between frames is calculated to obtain a moving map. Depending on the factor value from the moving map, the final image is obtained by reflecting the outputs of the RF- and CNN-based algorithms. If the factor value is high, the pixel intensity of the final image is like the CNN-based output, which is good for motion detection, and vice versa, it more reflects the intensity of RF output, which is excellent in perceptual quality. Therefore, it prevents motion blur and does not over-smooth microdetails, such as bones and muscles. The results show that combining the two outputs together records higher peak signal-to-noise ratio (PSNR) and has better perceptual quality for diagnosis than using only one method. F

关键词： Deep learning

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Coevolution of Myoelectric Hand Control under the Tactile Interaction among Fingers and Objects

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Cyborg and Bionic Systems 2022年第1期2022卷 285-302页

作者： Yuki Kuroda Yusuke Yamanoi Shunta Togo Yinlai Jiang Hiroshi Yokoi Joint Doctoral Program for Sustainability Research Graduate School of Informatics and Engineering The University of Electro-CommunicationsTokyoJapan Department of Mechan ical and Intelligent System Engineering Graduate School of Informatics and Engineering The University of Electro Communications TokyoJapan Center for Neuroscience and Biomedical Engineering The University of Electro Communications TokyoJapan Bejing Innovation Center for Inelligent Robots and Systems BeijingChina

The usability of a prosthetic hand difers significantly from that of a real ***,the complexity of manipulation increases as the number of degrees of freedom to be controlled increases,making manipulation with biological signals extremely *** overcome this problem,users need to select a grasping posture that is adaptive to the object and a stable grasping method that prevents the object from *** previous studies,these have been left to the operating skills of the user,which is extremely difficult to *** this study,we demonstrate how stable and adaptive grasping can be achieved according to the object regardless of the user's operation *** required grasping technique is achieved by determining the correlation bet ween the motor output and each sensor through the interaction between the prosthetic hand and the surrounding stimuli,such as myoelectricity,sense of touch,and grasping *** agents of the 16 DOF robot hand were trained with the myoelectric signals of six participants,including one child with a congenital forearm ***,each agent could open and close the hand in response to the myoeletric stimuli and could accomplish the object pickup *** the tasks,the agents successfully identified grasping patterns suitable for practical and stable positioning of the *** addition,the agents were able to pick up the object in a similar posture regardless of the partiipant,suggesting that the hand was optimized by evolutionary computation to a posture that prevents the object from being dropped.

关键词： robot Objects overcome

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View-Invariant Object Representation in Anterior and Posterior Inferotemporal Cortex: A Machine Learning Approach

SSRN

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SSRN 2025年

作者： Okamura, Jun-Ya Fukano, Daisuke Wang, Gang Information Science and Biomedical Engineering Program Graduate School of Science and Engineering Kagoshima University Kagoshima890-0065 Japan

Inferotemporal (IT) cortex is the final visual area in the ventral stream where object information is processed. Previous electrophysiological studies showed viewing angle tolerance of 30-60° of single IT cells to the objects experienced in discrimination at each of several viewing angles, and to the objects experienced in learning association of different views. IT is divided into anterior (cytoarchitectonic area TE) and posterior (TEO) parts. It was reported that single cells in area TE showed the viewing angle tolerance while those in area TEO did not. In the present study population activities were compared between cell populations in area TE and those in area TEO using machine learning algorithm. An object set consisted of four similar objects created by deforming a prototype object, and four views each separated by 30°. A population vector was created by aligning responses of the cells to each object image. A classifier was trained by support vector machine (SVM) to create a hyperplane that separated one object from the other three objects at the same viewing angles, and then tested by response vectors to the object images at different viewing angles. In area TE, dynamics of the performance evaluated by d’ showed viewing angle tolerance of 30-60° to the objects with prior experience in learning association of different views. In area TEO, populations of the cells did not show the viewing angle tolerance. Significant increase of the d’ values in area TE in the late time period for the objects with prior experience in learning association of different views may suggest view-invariance is more represented in late time period than early time period. These results suggest that viewpoint invariance is expressed more strongly in the TE region, providing new insights into the neural basis of object recognition © 2025, The Authors. All rights reserved.

关键词： Support vector machines

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Enhanced light-driven photoelectrochemical catalysis of water splitting by TiO2 nanotubes grown on acid-etched titanium foils

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International Journal of Hydrogen Energy 2024年第PartA期51卷 1483-1493页

作者： Hsiao, Yu-Cheng Lai, Jhih-Hong Fan, Yu-Min Chen, Hung-Ming Yougbaré, Sibidou Saukani, Muhammad Chen, Chih-Yu Wu, Yung-Fu Lin, Lu-Yin International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Stanford Byers Center for Biodesign Stanford University CA94305-5428 United States Graduate Institute of Biomedical Optomechatronics College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Gingen Technology Co. LTD. Rm. 7 10F. No.189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan /Nanoro 03 B.P 7192 Ouagadougou03 Burkina Faso Department of Mechanical Engineering Faculty of Engineering Universitas Islam Kalimantan MAB Jl. Adhyaksa No. 2 Banjarmasin70124 Indonesia Department of Orthopedics Shuang Ho Hospital Taipei Medical University New Taipei City23561 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei11696 Taiwan

Titanium dioxide with suitable band edges is one of promising photocatalysts for water splitting. Nanotubes with one-dimensional structure can induce efficient charge transfers and hollow centers can provide large surface area for surface reactions. Modifying Ti foils for anodization can enhance light utilization of TiO2 nanotube photoelectrodes. In this work, it is firstly to fabricate TiO2 nanotube photoelectrodes on acid-etched Ti foils by anodization (MNT) for photoelectrochemical catalyzing water splitting. Different acid-etching durations are applied on Ti foils to induce various rugged surfaces. The resulting photoelectrodes present largely enhanced light utilization than that fabricated by the pristine Ti foil. The anodization duration is also optimized to find suitable lengths of MNT. The smallest overpotential of 524.7 mV at 10 mA/cm2 and Tafel slope of 167 mV/dec are obtained for the optimal MNT photoelectrode. The TiO2 nanotubes grown on the pristine Ti foil shows the overpotential of 679.3 mV at 10 mA/cm2 and Tafel slope of 285 mV/dec. This result opens a blueprint for raising the photocatalytic ability by simply modifying the surface property of the conductive substrate. Other modifications may be applicable to enhance the roughness of Ti foils for growing more efficient MNT array as photocatalysis of water splitting. © 2023 Hydrogen Energy Publications LLC

关键词： Titanium dioxide

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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A novel label-free electrochemical immunosensor for the detection of heat shock protein 70 of lung adenocarcinoma cell line following paclitaxel treatment using l-cysteine-functionalized Au@MnO2/MoO3 nanocomposites

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RSC Advances 2023年第43期13卷 29847-29861页

作者： Chen, Yi-An Shie, Ming-You Ho, Chia-Che Ye, Sheng-Wen Chen, I.-Wen Peter Shih, Yu-Yin Shen, Yu-Fang Chen, Yi-Wen x-Dimension Center for Medical Research and Translation China Medical University Hospital Taichung City404332 Taiwan The Master Program for Biomedical Engineering China Medical University Taichung City406040 Taiwan Department of Biomedical Engineering China Medical University Taichung City40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung City41354 Taiwan Department of Chemistry National Cheng Kung University Tainan70101 Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung City40447 Taiwan

The future trend in achieving precision medicine involves the development of non-invasive cancer biomarker sensors that offer high accuracy, low cost, and time-saving benefits for risk clarification, early detection, disease detection, and therapeutic monitoring. A facile approach for the synthesis of MoO3 nanosheets was developed by thermally oxidizing MoS2 nanosheets in air followed by thermal annealing. Subsequently, Au@MnO2 nanocomposites were prepared using a combined hydrothermal process and in situ chemical synthesis. In this study, we present a novel immunosensor design strategy involving the immobilization of antiHSP70 antibodies on Au@MnO2/MoO3 nanocomposites modified on a screen-printed electrode (SPE) using EDC/NHS chemistry. This study establishes HSP70 as a potential biomarker for monitoring therapeutic response during anticancer therapy. Impedance measurements of HSP70 on the Au@MnO2/MoO3/SPE immunosensor using EIS showed an increase in impedance with an increase in HSP70 concentration. The electrochemical immunosensor demonstrated a good linear response in the range of 0.001 to 1000 ng mL−1 with a detection limit of 0.17 pg mL−1 under optimal conditions. Moreover, the immunosensor was effective in detecting HSP70 at low concentrations in a lung adenocarcinoma cell line following Paclitaxel treatment, indicating its potential for early detection of the HSP70 biomarker in organ-on-a-chip and clinical applications. © 2023 The Royal Society of Chemistry.

关键词： Nanosheets

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Generalize or Specialize? The Effect of Coil Combining in Deep Learning Based MR Image Reconstruction

Generalize or Specialize? The Effect of Coil Combining in De...

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IEEE International Symposium on biomedical Imaging

作者： Natalia Dubljevic Richard Frayne Roberto Souza Biomedical Engineering Graduate Program Hotchkiss Brain Institute University of Calgary Calgary AB Canada Seaman Family MR Research Centre Foothills Medical Centre Calgary AB Canada Biomedical Engineering Graduate Program Radiology Clinical Neurosciences Hotchkiss Brain Institute University of Calgary Calgary AB Canada Biomedical Engineering Graduate Program Electrical and Software Engineering Hotchkiss Brain Institute University of Calgary Calgary AB Canada

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

With the advent of deep-learning based MR image reconstruction, new questions are raised regarding best design choices. In particular, when using recent reconstruction models that have been developed for processing multi-channel MR data. A fundamental question is whether to first combine channels to improve model generalizability (i.e., a “coil-combined” approach) or to keep channel processing separate to fully utilize multi-channel information (i.e., an “all-coil” approach). In this work, we compare three popular architectures using coil-combined and all-coil styles on brain MR images. All-coil styles improved in-distribution performance, such as when reconstructing only presumed healthy individu-als. Coil-combined designs better generalized to unseen data from patients with pathology.

关键词： Deep learning Coils Pathology Codes Magnetic resonance Brain modeling Data models Image reconstruction biomedical imaging

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Pathogen inhibition and indication by gelatin nonwoven mats with incorporation of polyphenol derivatives

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RSC Advances 2023年第45期13卷 31602-31615页

作者： Bai, By Meng-Yi Wang, Ting-Teng Chen, Xin-An Wu, Chia-Chun Graduate Institute of Biomedical Engineering and Biomedical Engineering Program Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology TR-917 AAEON Building No. 43 Keelung Rd. Sec. 4 Da'an Dist. Taiwan Taipei City10607 Taiwan Adjunct Appointment to the National Defense Medical Center Taiwan Taipei11490 Taiwan Institute of Prevention Medicine National Defense Medical Center Taiwan Taipei11490 Taiwan

There is a need for non-pharmaceutical intervention methods that can prevent and indicate the risk of airborne disease spread. In this study, we developed a nonwoven mat based on the polyphenol gallic acid, which can inhibit pathogens growth and also indicate pathogen levels in the surrounding environment. Using nuclear magnetic resonance, Fourier-transform infrared spectroscopy, and high-performance liquid chromatography, we characterized this novel gelatin-based nonwoven mat and investigated the mechanism governing its ability to indicate pathogen levels. We demonstrated that the incorporation of gallic acid serves a vital role in indicating the presence of bacteria, causing the nonwoven mat to change in color from white to brown. We have proposed a plausible mechanism for this color change behavior based on a reaction of gallic acid with components excreted by bacteria, including glutamate, valine, and leucine. The concentrations of these components reflect the bacterial counts, enabling a real-time indication of pathogen levels in the surrounding air. In summary, the nonwoven mat presented herein can serve as an excellent antibacterial agent and as an indicator of nearby bacteria for fabricating personal protection equipment like filtration mask. © 2023 The Royal Society of Chemistry.

关键词： Bacteria

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