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Deepepiil13: Deep Learning for Prediction of Il-13 Inducing Epitopes Using Pre-Trained Language Models and Multi-Window Convolutional Neural Networks

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SSRN 2024年

作者： Chuang, Cheng-Che Ou, Yu-Yen Department of Computer Science and Engineering Yuan Ze University Chung-Li32003 Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Chung-Li32003 Taiwan

Interleukin-13 (IL-13) is a key cytokine involved in allergic inflammation and the cytokine storm associated with severe COVID-19. Identifying antigenic epitopes capable of inducing IL-13 holds therapeutic potential for developing epitope-based vaccines and immunomodulatory treatments. However, conventional methods for epitope prediction are often inefficient and inaccurate. This study presents DeepEpiIL13, a novel deep learning framework that integrates pre-trained language models and multi-window convolutional neural networks (CNNs) to rapidly and accurately predict IL-13-inducing epitopes from protein sequences. The ProtTrans pre-trained language model was employed to generate high-dimensional embeddings that capture rich contextual information from protein sequences. These embeddings were then inputted into a multi-window CNN architecture, enabling the efficient exploration of local and global sequence patterns associated with IL-13 induction. The proposed approach was rigorously evaluated using benchmark datasets and an independent SARS-CoV-2 dataset. DeepEpiIL13 achieved superior performance compared to traditional methods, with an impressive Matthews correlation coefficient (MCC) of 0.52 and an area under the receiver operating characteristic curve (AUC) of 0.86 on the benchmark dataset. On the independent SARS-CoV-2 dataset, DeepEpiIL13 demonstrated remarkable robustness, attaining an MCC of 0.63 and an AUC of 0.92, highlighting its potential applicability in the context of COVID-19 research. This study introduces a powerful deep learning framework for accurate epitope prediction, offering new avenues for the development of epitope-based vaccines and immunotherapies targeting IL-13-mediated disorders. The successful identification of IL-13-inducing epitopes paves the way for novel therapeutic interventions against allergic diseases, inflammatory conditions, and potentially severe viral infections like COVID-19. © 2024, The Authors. All rights reserved.

关键词： COVID-19

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pH/GSH dual responsive nanosystem for nitric oxide generation enhanced type I photodynamic therapy

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Bioactive Materials 2024年第4期34卷 414-421页

作者： Jianhua Zou Zheng Li Yang Zhu Yucen Tao Qing You Fangfang Cao Qinghe Wu Min Wu Junjie Cheng Jianwei Zhu Xiaoyuan Chen Departments of Diagnostic Radiology SurgeryChemical and Biomolecular Engineeringand Biomedical EngineeringYong Loo Lin School of Medicine and College of Design and EngineeringNational University of SingaporeSingapore119074Singapore Nanomedicine Translational Research Program NUS Center for NanomedicineYong Loo Lin School of MedicineNational University of SingaporeSingapore117597Singapore Clinical Imaging Research Centre Centre for Translational MedicineYong Loo Lin School of MedicineNational University of SingaporeSingapore117599Singapore Institute of Molecular and Cell Biology Agency for ScienceTechnologyand Research(A*STAR)61 Biopolis DriveProteosSingapore138673Singapore Department of Plastic and Reconstructive Surgery Shanghai Ninth People’s HospitalShanghai Jiaotong UniversityShanghai200011PR China Department of Chemistry Center for Bioanalytical Chemistry University of Science and Technology of ChinaHefei230026PR China College of Life Science Nanjing Normal University1 Wenyuan RoadNanjing210023PR China

Tumor hypoxia diminishes the effectiveness of traditional type II photodynamic therapy(PDT)due to oxygen *** I PDT,which can operate independently of oxygen,is a viable option for treating hypoxic *** this study,we have designed and synthesized JSK@PEG-IR820 NPs that are responsive to the tumor microenvironment(TME)to enhance type I PDT through glutathione(GSH)*** approach aims to expand the sources of therapeutic benefits by promoting the generation of superoxide radicals(O_(2)^(-).)while minimizing their *** diisopropyl group within PEG-IR820 serves a dual purpose:it functions as a pH sensor for the disassembly of the NPs to release JSK and enhances intermolecular electron transfer to IR820,facilitating efficient O_(2)^(-).***,the release of JSK leads to GSH depletion,resulting in the generation of nitric oxide(NO).This,in turn,contributes to the formation of highly cytotoxic peroxynitrite(ONOO^(-).),thereby enhancing the therapeutic efficacy of these ***-II fluorescence imaging guided therapy has achieved successful tumor eradication with the assistance of laser therapy.

关键词： TME responsive NO gas therapy NIR-II imaging Type I PDT

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Enhancing the Performance of E-Mode AlGaN/GaN HEMTs With Recessed Gates Through Low-Damage Neutral Beam Etching and Post-Metallization Annealing

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 150-155页

作者： Chen, Yi-Ho Ohori, Daisuke Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan Tohoku University Institute of Fluid Science Sendai980-8577 Japan 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 Pioneer Semiconductor Innovation Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300093 Taiwan

This study investigated the electrical properties of AlGaN/GaN high-electron-mobility transistors (HEMTs) with varied recess depths under the gate electrode. We demonstrated a recess depth of approximately 6 nm, which was achieved through neutral beam etching (NBE) technique with a low etch rate of 1.8 nm/min, resulting in device enhancement-mode (E-mode) behavior with threshold voltage (Vth) of 0.49 V. The effects of post-metallization annealing (PMA) on the device performance were also examined. The results revealed that PMA treatment improves the DC characteristics of the devices, including maximum drain current (IDMAX), transconductance (gm), subthreshold swing (SS), on-off ratio, and off-state leakage current, with maximum enhancement percentage of 18.3% for IDMAX, 3758% for on-off ratio, and 54.3% for SS. Moreover, this study compared the recess depths of metal-insulator-semiconductor high-electron-mobility transistors (MIS-HEMTs) with the SiN dielectric layer. The results showed that MIS-HEMTs exhibit more negative Vth values, which can be attributed to the controlled surface states achieved through passivation. © 2020 IEEE.

关键词： Etching

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Flexible organic solar cells for biomedical devices

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Nano Research 2021年第9期14卷 2891-2903页

作者： Bin Kan Faheem Ershad Zhoulyu Rao Cunjiang Yu Department of Mechanical Engineering University of HoustonHoustonTX 77204USA Department of Biomedical Engineering University of HoustonHoustonTX 77204USA Materials Science and Engineering Program University of HoustonHoustonTX 77204USA Department of Electrical and Computer Engineering University of HoustonHoustonTX 77204USA Texas Center for Superconductivity University of HoustonHoustonTX 77204USA

Organic solar cells(OSCs),particularly made based on solution processing methods,have made significant progress over the past decades through the concurrent evolution of organic photovoltaic materials and device ***,high power conversion efficiencies around 18%and over 16%have been demonstrated in both rigid and flexible OSCs,*** most of the OSC research has centered on efficiency and cost,their emerging and potential usages in many critical applications,particularly in biomedical fields have been *** this mini-review,we will briefly discuss the high-performance organic photovoltaic materials and the representative flexible OSCs to give a scope on the recent rapid development of ***,we will review some progress on the applications of OSCs in biomedical devices and integrated *** potential challenges associated with integrating OSCs for biomedical devices will be put forward.

关键词： organic solar cells photovoltaic flexible biomedical bioelectronics

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Identifying Prognostic Markers of Non-small Cell Lung Carcinoma Using Bioinformatics

Identifying Prognostic Markers of Non-small Cell Lung Carcin...

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International Conference on Industrial Instrumentation and Control,ICI2C 2021

作者： Khan, Siladitya Chakraborty, Debamitra Department of Biomedical Engineering University of Rochester RochesterNY14627 United States Goergen Institute for Data Science University of Rochester RochesterNY14627 United States Materials Science Graduate Program University of Rochester RochesterNY14627 United States

ISBN: (纸本)9789811670107

We present a transcriptomics pipeline for performing the functional analysis of array expression profiling data of normal and adenocarcinoma lung tissue. Our aims are twofold, firstly to elucidate molecular processes that transform normal tissue, to a lung adenocarcinoma. Following this, we perform functional analysis to screen potential hub genes and demonstrate their value in cancer prognosis. Analysis was performed on a total of 500 differentially expressed genes (DEG), screened for their regulation and transcriptional modulation in a female population carrying non–small cell lung carcinoma (NSCLC). Key pathways like cytokine-cytokine receptors, ECM receptor interactions, and TNF signaling were identified suggesting a potential role in lung tumorigenesis. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Bioinformatics

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A Transparent Ultrasound Array for Real-Time Optical,Ultrasound,and Photoacoustic Imaging

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biomedical engineering Frontiers 2022年第1期3卷 284-297页

作者： Haoyang Chen Sumit Agrawal Mohamed Osman Josiah Minotto Shubham Mirg Jinyun Liu Ajay Dangi Quyen Tran Thomas Jackson Sri-Rajasekhar Kothapalli Department of Biomedical Engineering The Pennsylvania State UniversityUniversity ParkPA 16802USA School of Electrical Engineering and Computer Science The Pennsylvania State UniversityUniversity ParkPA 16802USA Penn State Cancer Institute The Pennsylvania State UniversityHersheyPA 17033USA Graduate Program in Acoustics The Pennsylvania State UniversityUniversity ParkPA 16802USA

Objective and Impact *** imaging of ultrasound and optical contrasts can help map structural,functional,and molecular biomarkers inside living subjects with high spatial *** is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and ***,combining ultrasound,photoacoustic,and optical imaging modalities is challenging because conventional ultrasound transducer arrays are optically *** a result,complex geometries are used to coalign both optical and ultrasound waves in the same field of *** elegant solution is to make the ultrasound transducer transparent to ***,we demonstrate a novel transparent ultrasound transducer(TUT)linear array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal *** TUT-array consists of 64 elements and centered at~6 MHz *** demonstrate a quad-mode ultrasound,Doppler ultrasound,photoacoustic,and fluorescence imaging in real-time using the TUT-array directly coupled to the tissue mimicking *** TUT-array successfully showed a multimodal imaging capability and has potential applications in diagnosing cancer,neurological,and vascular diseases,including image-guided endoscopy and wearable imaging.

关键词： Ultrasound specificity transparent

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Enhancing wound healing and adhesion through dopamine-assisted gelatin-silica hybrid dressings

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International Journal of Biological Macromolecules 2024年第Part2期258卷 128845页

作者： Lin, Yu-Chien Wang, Huey-Yuan Tang, Yao-Chun Lin, Wan-Rong Tseng, Ching-Li Hu, Chih-Chien Chung, Ren-Jei Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei10608 Taiwan School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Department of Stomatology MacKay Memorial Hospital Taipei104217 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 Bone and Joint Research Center Chang Gung Memorial Hospital Linkou33305 Taiwan Taipei10608 Taiwan

Gelatin, widely employed in hydrogel dressings, faces limitations when used in high fluid environments, hindering effective material adhesion to wound sites and subsequently reducing treatment efficacy. The rapid degradation of conventional hydrogels often results in breakdown before complete wound healing. Thus, there is a pressing need for the development of durable adhesive wound dressings. In this study, 3-glycidoxypropyltrimethoxysilane (GPTMS) was utilized as a coupling agent to create gelatin-silica hybrid (G-H) dressings through the sol-gel method. The coupling reaction established covalent bonds between gelatin and silica networks, enhancing structural stability. Dopamine (DP) was introduced to this hybrid (G-H-D) dressing to further boost adhesiveness. The efficacy of the dressings for wound management was assessed through in-vitro and in-vivo tests, along with ex-vivo bioadhesion testing on pig skin. Tensile bioadhesion tests demonstrated that the G-H-D material exhibited approximately 2.5 times greater adhesion to soft tissue in wet conditions compared to pure gelatin. Moreover, in-vitro and in-vivo wound healing experiments revealed a significant increase in wound healing rates. Consequently, this material shows promise as a viable option for use as a moist wound dressing. © 2023

关键词： Adhesion

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DCGAN-based Medical Image Augmentation to Improve ELM Classification Performance 11

DCGAN-based Medical Image Augmentation to Improve ELM Classi...

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Rando Setiawan, Noor Akhmad Permanasari, Adhistya Erna Rulaningtyas, Riries Suksmono, Andriyan Bayu Sitanggang, Imas Sukaesih Universitas Gadjah Mada Dept. of Electrical and Information Engineering Yogyakarta Indonesia Biomedical Engineering Program Dept. of Physics Universitas Airlangga Surabaya Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Ipb University Department of Computer Science Bogor Indonesia

ISBN: (纸本)9781665460309

Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%. © 2022 IEEE.

关键词： Generative adversarial networks

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Lung Nodule Analysis in CT Images: Deep Learning for Segmentation and Measurement 24

Lung Nodule Analysis in CT Images: Deep Learning for Segment...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Li, Ai-Hsien Adams Aruperes, Cristian Daniel Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Division of Cardiology Far Eastern Memorial Hospital New Taipei TaiwanGraduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan TaiwanInnovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan TaiwanGraduate Institute of Medicine Yuan Ze University Taoyuan Taiwan TaiwanDepartment of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400716874

In the realm of research, the global health challenge posed by lung cancer remains pronounced, contributing substantially to annual cancer-related fatalities. The critical imperative lies in the early identification of pulmonary nodules, frequently indicative of impending lung cancer, to enhance patient outcomes and diminish mortality rates. Computed Tomography (CT) imaging stands out as a pivotal diagnostic instrument for the timely detection of these nodules. The swift proliferation of medical imaging data has underscored the pressing necessity for precise and efficient methodologies dedicated to nodule segmentation and measurement. These approaches are crucial in assisting radiologists in their diagnostic and clinical decision-making endeavors. In this study, we introduced a thorough method for analyzing lung nodules, leveraging dataset from Far Eastern Memorial Hospital (FEMH) comprising original CT images and manually annotated ground truth masks obtained with the assistance of radiologists at FEMH. This dataset is utilized for the segmentation of nodules. We employed advanced deep learning models, specifically the U-Net architecture, identified as the optimal model through our training process. We made substantial progress in nodule segmentation, attaining an Intersection over Union (IoU) score of 0.824 and a Dice Coefficient of 0.903 for the FEMH dataset. Furthermore, our performance improved when utilizing the merged dataset comprising FEMH and Luna16, yielding an IoU score of 0.862 and a Dice Coefficient of 0.926. Luna16 has been extensively utilized in numerous studies related to nodule detection and segmentation. In the next phase of the study, the best-performing model from our segmentation phase was utilized to predict nodule masks on the merged dataset. Subsequently, we measured the size of each predicted nodule by comparing it with the size ground truth mask in millimeters. In detail, this study achieved the Pearson Correlation Coefficient (PCC) at 0.

关键词： Computerized tomography

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Modifying BiVO4 as a photocatalyst for water oxidation using constant-duration alkaline-etched post treatments

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New Journal of Chemistry 2023年第2期48卷 569-577页

作者： Hsu, Chuan-Chih Chuang, Kai-Jie Huang, Hsiao-Wen Pan, Bo-Jin Chen, Hung-Ming Husain, Sadang Yougbaré, Sibidou Hsiao, Yu-Cheng Wu, Yung-Fu Lin, Lu-Yin Division of Cardiovascular Surgery Department of Surgery School of Medicine College of Medicine Taipei Medical University Taiwan Division of Cardiovascular Surgery Department of Surgery Taipei Medical University Hospital 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 Department of Physics Faculty of Mathematics and Natural Science Lambung Mangkurat University Banjarmasin70124 Indonesia /Nanoro Ouagadougou03 Burkina Faso 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 Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei11696 Taiwan

BiVO4 with suitable band edges and a small band gap is considered an efficient photocatalyst for the oxygen evolution reaction (OER), but short charge-transfer lengths limit its photocatalytic ability. Increasing active sites can essentially enhance oxidation reactions and photocatalytic ability. The alkaline etching technique can refine the surface properties of BiVO4 by introducing oxygen vacancies and possibly establishing a heterojunction, but suitable alkaline etching methods are rarely discussed. In this study, three alkaline etching methods, including hydrothermal, soaking, and electrodeposition processes, are first applied for a constant duration to tailor the surface properties of BiVO4 as a photocatalyst for the OER. Alkaline-etched BiVO4 prepared using hydrothermal and soaking processes shows better photocatalytic abilities due to the generation of additional oxygen vacancies, while poor photocatalytic ability is found for that fabricated using electrodeposition due to the formation of less photocatalytic VO2. The highest photocurrent density of 2.38 mA cm−2 is obtained at 1.23 V versus a reversible hydrogen electrode in an electrolyte without a hole scavenger for the BiVO4 etched in the hydrothermal process, while the untreated BiVO4 presents a photocurrent density of 0.58 mA cm−2. A photocurrent retention of 92.3% is achieved after 5000 seconds of continuous illumination. The study supplies blueprints for establishing effective alkaline etching methods for enhancing the photocatalytic ability of BiVO4, with the exception of time costs. © 2024 The Royal Society of Chemistry.

关键词： Charge transfer

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