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Transactions of Japanese Society for Medical and Biological engineering 2021年第Proc期Annual59卷 694-696页

作者： Shimazaki, Naoya Shin’e, Yoshimasa Oku, Tomoko Yamauchi, Shinobu Motohashi, Yuka Sato, Toshio Department of Clinical Engineering Faculty of Health Science Gunma Paz University Japan Graduate School of Engineering Toin University of Yokohama Japan Department of Clinical Engineering Faculty of Biomedical Engineering Toin University of Yokohama Japan

(Introduction) In blood purification therapy, contact between foreign particles and the blood can activate blood coagulation factors or platelets. Consideration of the effects of differences in chamber geometry has generally been absent from reports on standardization of hemodialysis circuits, even though blood coagulation tends to occur in the venous air-trap chamber of a hemodialysis circuit because of both exposure of blood to internal air and delay or stagnation of blood flow. We considered that improving the filter and blood inflow design to control eddy formation and pooling and reduce the duration of blood pooling could potentially reduce coagulation in the chamber. In the present study, a theoretical investigation of the effects of chamber design parameters on coagulation was performed using computational fluid dynamics (CFD), and the appropriateness of CFD analysis was evaluated through visualization of the flow using particle image velocimetry (PIV). © 2021, Japan Soc. of Med. Electronics and Biol. engineering. All rights reserved.

关键词： Computational fluid dynamics

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Electronically Scanned Large Apertures for Interventional and Diagnostic Liver

Electronically Scanned Large Apertures for Interventional an...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Wodnicki, Robert Zhang, Junhang Zhou, Qifa Foiret, Josquin Notard, Christophe Ferrara, Katherine W. University of Southern California Dept. of Biomedical Engineering Los AngelesCA United States Molecular Imaging Program Stanford University StanfordCA United States Vermon S.A. Tours France

ISBN: (纸本)9798350346459

We have developed a handheld 1,024-element large area 2D array probe integrated with high voltage multiplexing ASIC modules with row-multiplexed imaging in orthogonal azimuthal and elevational planes with image data computed and displayed on a commercially available 32 channel configurable ultrasound system. Here we demonstrate real-time orthogonal imaging of small structures at high resolution in water with the 1,024-element array. We have also integrated modular imaging electronics with a newly designed 4,096-element 4 times larger aperture acoustic array (83 mm × 16 mm aperture with 650 μm azi. × 500 μm elev. element pitch) with 128 elements in azimuth and 32 rows in elevation. The two arrays were interfaced to an open-platform ultrasound imaging system using custom-designed multiplexing ASICs and imaged with plane waves at Fc = 2.5 MHz. © 2023 IEEE.

关键词： Synthetic apertures

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Building a Brain Computer Interface (BCI) Using Electroencephalogram (EEG) Signals' Classification

Building a Brain Computer Interface (BCI) Using Electroencep...

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International Conference on Advances in biomedical engineering (ICABME)

作者： Mohammad Nabil Younis Sary Haj Sleiman Salma Khadra Amira Zaylaa Alaa Daher Mohammad Ayache Depatment of Electrical and Computer Engineering Beirut Arab University Biomedical Program Debbieh Lebanon

Development of Brain Computer Interface (BCI) has been rapid since the mid 1990‘s. There are three criteria for BCI, (i) comfortability and possession of a suitable signal acquisition device, (ii) system validation and dissemination, and (iii) reliability and potentiality. As there are no BCI possessing the optimal criteria, it was essential to consider building a new one. Thereby, the paper investigates building BCI based on the utilization of EEG signals to translate brainwave patterns into actionable commands. The primary objective is to enhance communication capabilities for individuals afflicted with neurological disorders, empowering them to command external devices and engage more effectively with their surroundings. We built our model on EEG online dataset for the purpose of feature extraction and classification. Statistical features and Discrete Wavelet Transform (DWT) have been applied for feature selection. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) were the classifiers involved. Results showed that the proposed architecture of MLP and RBF were able to classify the EEG signals into two classes (open eye and closed eye). Results also showed that the proposed approach, which is based on the combination of statistical features and DWT for features selection using AF3 and AF4 channels by the application of MLP, has 98% succession rate. BCI system based on Arduino circuit has been built after the classification Further algorithms and system evaluation need to be considered as future work.

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The Signal Synchronization Function of Myelin

arXiv

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arXiv 2024年

作者： Yu, Zhuonan Qin, Peijun Sun, Ruibing Khademi, Sara Xu, Zhen Sun, Qinchao Tai, Yanlong Song, Bing Guo, Tianruo Wang, Hao Shenzhen518035 China Graduate School of Biomedical Engineering University of New South Wales SydneyNSW2052 Australia

The myelinated axons widely present in both central and peripheral nervous systems1,2. Its unique compact spiraling structure poses significant challenges for understanding its biological functions and developmental mechanisms3. Conventionally, myelin is considered as in insulating layer to achieve saltatory conduction for the enhancement of the neural signal speed4, which serves as the foundation of neuroscience5. However, this insulating hypothesis is inadequate to account for a various experimental observations6-11, especially the long unmyelinated tract observed in cortex12,13. We here show non-random distributions in three ultrastructural features of myelin: the non-random spiraling directions, the localization preferences of myelin's outer tongues, and the radial components along boundaries between oppositely spiraled myelin sheaths. These phenomena are predicted by a novel concept of myelin's biological function, which we propose as the "signal synchronization function." Our findings demonstrate that cytoplasmic channels within myelin may act as coiled inductors, facilitating electromagnetic induction between adjacent myelin sheaths, thereby promoting signal synchronization between axons. This, in turn, explains the non-random ultrastructural features observed. We believe these insights lay the foundation for a new understanding of myelin's inductive function. This perspective could significantly reshape the textbook understanding of myelin and the nervous system by introducing several key points:1. myelin may function as a micro-coil, engaging magnetic fields in neural signaling;2. axons may not transmit neural signals independently, but instead form clusters to synchronize signal transmission;3. this work provides a clear principle for how electric and magnetic fields influence myelin development, potentially revolutionizing research into myelin regeneration and rehabilitation through electrical and magnetic modulation. © 2024, CC BY.

关键词： Electromagnetic induction

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Effects of various parameters on guidewire and catheter behavior during catheter introduction

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Journal of Biomechanical Science and engineering 2025年第1期20卷 1-15页

作者： TAKASHIMA, Kazuto HIDAKA, Hiroto NAMBA, Akinori HAGA, Yoichi OHTA, Makoto MORI, Koji TOMA, Naoki SHOJIMA, Masaaki Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology 2-4 Hibikino Wakamatsu-ku Kitakyushu Fukuoka808-0196 Japan Graduate School of Biomedical Engineering Tohoku University 6-6 Aza-Aoba Aramaki Aoba-ku Sendai Miyagi980-8579 Japan Institute of Fluid Science Tohoku University 2-1-1 Katahira Aoba-ku Sendai Miyagi980-8577 Japan Graduate School of Sciences and Technology for Innovation Yamaguchi University 2-16-1 Tokiwadai Ube Yamaguchi755-8611 Japan Graduate School of Medicine Mie University 2-174 Edobashi Tsu Mie514-8507 Japan Graduate School of Medicine Teikyo University 2-11-1 Kaga Itabashi-Ku Tokyo173-8606 Japan

Many guidewire penetration accidents occur during catheter introduction. Therefore, we have evaluated the behavior of medical devices such as guidewires and catheters during catheter introduction using numerical simulations. In our previous study, we evaluated the effects of the insertion velocity of the guidewire and the catheter and confirmed that during catheter introduction, the guidewire imparted a greater load on the vessel wall than that exerted by the guidewire alone. However, it was unclear whether the above phenomenon could also occur under other conditions. In the present study, in addition to these effects, we evaluate the effects of the blood vessel elastic modulus, device insertion length, blood vessel centerline curvature, and their interactions. Furthermore, we evaluate the behavior of the medical devices during guidewire removal after catheter introduction, which was not evaluated in our previous study. We determine the simulation conditions based on the design of experiments and investigate the dominant parameters that affect the contact force between the medical devices and the blood vessel wall using two methods (one that considers parameter interactions and one that does not). We confirm that during guidewire insertion and removal, the device velocity and the vessel centerline curvature have the largest effects, respectively. For the guidewire and the catheter during catheter introduction, the vessel elastic modulus and the insertion velocity have the largest effects, respectively, and the parameter interactions have large effects. These findings are clinically important because they are counterintuitive. During catheter introduction, the average contact forces are larger than those during both guidewire insertion and removal. Furthermore, during guidewire removal, the catheter tip moves in the distal direction. © 2025 The Japan Society of Mechanical Engineers

关键词： Catheter tip sensors

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Towards Precision Cancer Therapy: Prottrans and Multi-Window Scanning Convolutional Neural Networks Transforming Protein-Peptide Interaction Predictions

SSRN

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SSRN 2024年

作者： Van Le, The Zi Zhan, Jun Yu Ou, Yen Department of Computer Science and Engineering Yuan Ze University Chung-Li32003 Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Chung-Li32003 Taiwan

This study delves into the prediction of protein-peptide interactions using advanced machine learning techniques, comparing models such as sequence-based, standard CNNs, and traditional classifiers. Leveraging pre-trained language models and multi-view window scanning CNNs, our approach yields significant improvements, with ProtTrans standing out based on 2.1 billion protein sequences and 393 billion amino acids. The integrated model achieves an impressive AUC of 0.855 and 0.822 on Set_1 and Set_2 datasets, outperforming previous methods. Beyond this, we explore the application of this model in cancer therapy, particularly in identifying peptide interactions for selective targeting of cancer cells. The findings of this study contribute to bioinformatics, providing valuable insights for drug discovery and therapeutic development. © 2024, The Authors. All rights reserved.

关键词： Machine learning

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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

SSRN

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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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A CNN-based Image Reconstruction Scheme for Complex-valued Multi-frequency Electrical Capacitance Tomography 4

A CNN-based Image Reconstruction Scheme for Complex-valued M...

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4th IEEE International Conference on Electrical Materials and Power Equipment, ICEMPE 2023

作者： Xiong, Yifei Zhu, Liying Zhang, Maomao Wang, Zheming Liu, Yongsheng Lu, Wu Shanghai University of Electric Power School of Electrical Engineering Shanghai China City University of Hong Kong Department of Biomedical Engineering Hong Kong Tsinghua Shenzhen International Graduate School Shenzhen China Insititute of Solar Energy Shanghai University of Electric Power Shanghai China

ISBN: (纸本)9798350334678

Complex-valued multi-frequency electrical capacitance tomography (CVMF-ECT) is a newly developed imaging method for both industrial and medical applications, such as non-invasive fault detection and multi-phase flow measurement. It can simultaneously reconstruct spectra conductivity and permittivity properties of testing object within the region of interest (ROI), which can reveal more characteristics of conductive samples compared to the traditional single-frequency ECT. However, currently CVMFECT is still in small-scale trials, since the traditional iterative algorithms used by CVMF-ECT to reconstruct images have numerous iteration times and slow imaging speeds, result in poor imaging qualities. In this paper, an image reconstruction network namely SegNet is employed to effectively utilize the relationships between multi-frequency spectra data and the real distributions of dielectrics. Numerical simulations validate the superior performance of SegNet compared with traditional imaging reconstruction approaches such as Local Binary Patterns and Tikhonov Regularization. © 2023 IEEE.

关键词： Complex networks

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Enhancement of Swimming Endurance by Herbal Supplement M3P

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Chinese Journal of Integrative Medicine 2022年第8期28卷 725-729页

作者： CHU Chien-ming CHI Chih-wen HUANG Chih-hung CHEN Yu-jen Graduate Institute of Biochemical and Biomedical Engineering National Taipei University of TechnologyTaipeiTaiwan10608China BioMedical Development Center MacKay Memorial HospitalNew Taipei CityTaiwan25160China Department of Medical Research MacKay Memorial HospitalNew Taipei CityTaiwan25160China Department of Radiation Oncology MacKay Memorial HospitalTaipeiTaiwan10449China

Objective:To investigate the effect of M3P(containing Deer antler,Cordyceps sinensis,Rhodiola rosea,and Panax ginseng);an herbal remedy with the function of tonifying Kidney(Shen)and invigorating Spleen(Pi),replenishing qi and nourishing blood;on fatigue alleviation,endurance capacity and ***:Swimming with weight-loading of 24 male ICR mice was used to evaluate the endurance capacity,and fatiguerelated plasma biomarkers were *** were randomly assigned to control or M3P treatment groups with 6 mice for each group and were orally administered with M3P everyday for 8 weeks at doses 0,10,33 or 100 mg/*** time to exhaustion was measured in a specialized water *** and kidney functions,body weight,and hematological profile were determined to evaluate the safety and toxicity after long-term M3P ***:M3P supplementation 100 mg/kg significantly increased swimming endurance time up to approximate 2.4 folds of controls(P<0.05).The plasma concentrations of cortisol and hepatic glycogen content were significantly increased in mice received M3P(P<0.05,P<0.01 respectively).The lactic acid level and blood glucose were not changed after M3P treatment(P>0.05).The liver and kidney functions muscle damage biomarker creatine,body weight,and hemograms were not altered in M3P supplementation(P>0.05).Conclusion:M3P supplementation may improve swimming endurance accompanied by increasing hepatic glycogen content and serum cortisol level without major toxicity.

关键词： swimming endurance fatigue tonifying Kidndy(Shen)and invigorating Spleen(Pi) replenishing qi and nourishing blood M3P mice Chinese medicine

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Nanoarchitectonics of point-of-care diagnostics for sweat biomarkers analysis

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Nano Materials Science 2024年第6期6卷 647-671页

作者： Xuan Lin Arya Vasanth Aditya Ashok Hoang-Phuong Phan Kevin M.Koo Mohammed A.Amin Yusuf Valentino Kaneti Carlos Salomon Md Shahriar A.Hossain Yusuke Yamauchi Mostafa Kamal Masud School of Chemistry and Molecular Biosciences The University of QueenslandBrisbaneQLD4072Australia Australian Institute of Bioengineering and Nanotechnology The University of QueenslandBrisbaneQLD4076Australia Graduate School of Biomedical Engineering The University of New South WalesSydneyNSW2052Australia The University of Queensland Centre for Clinical Research(UQCCR) HerstonQueensland4029Australia Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Translational Extracellular Vesicles in Obstetrics and Gynae-Oncology Group University of Queensland Centre for Clinical ResearchFaculty of MedicineThe University of QueenslandBrisbaneQLD 4029Australia School of Mechanical and Mining Engineering Faculty of EngineeringArchitecture and Information Technology(EAIT)The University of QueenslandBrisbaneQLD4072Australia Department of Materials Process Engineering Graduate School of EngineeringNagoya UniversityFuro-choChikusa-kuNagoyaAichi464-8603Japan Department of Chemical and Biomolecular Engineering Yonsei UniversitySeoul 03722South Korea

Sweat contains numerous vital biomarkers such as metabolites,electrolytes,proteins,nucleic acids and antigens that reflect hydration status,exhaustion,nutrition,and physiological *** healthcare diagnosis relies on disease diagnostics in sophisticated centralized laboratories with invasive sample collection(e.g.,chemical analyses,plasma separation via centrifugation,tissue biopsy,etc.).Cutting-edge point-of-care diagnostics for sweat biomarker analysis allow for non-invasive monitoring of physiologically related biomarkers in sweat and real-time health status ***,using advanced nanoarchitectures,including nanostructured platforms and nanoparticles,can enhance the specificity,sensitivity,wearability and widen the sensing modality of sweat ***,we comprehensively review the secretory mechanisms,clinical uses of sweat biomarkers,and the design,principle,and latest technologies of sweat *** an emphasis on cutting-edge technologies for sweat biomarker analysis,this review chronicles the issues associated with the current sweat biomarkers analysis of sweat biomarkers and provides insights into strategies for enhancing the translation of such biosensors into routine clinical practice.

关键词： Sweat biomarker Nanoarchitectonics Nanostructures Sweat biosensor Point-of-care diagnostics Wearable sweat sensor

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