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3rd IEEE Eurasia Conference on biomedical engineering, Healthcare and Sustainability, ECBIOS 2021

作者： Zida, Serge Ismael Lin, Yue-Der Lee, Cheng Lin Tsai, Yi Lun Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9781728193045

The evolution of medical technology along with information and communication technologies has accelerated the development and operationalization of smart hospitals recently. Traditionally, such hospitals typically rely on cloud computing platforms for data treatment and processing. However, the expansion and popularization of Internet of Medical Things (IoMT) devices and constant data monitoring have resulted in massive amounts of generated data, leading to the overload of the cloud infrastructure. This results in high power consumption and latency in data transmission, which is critical especially in a healthcare environment where data flow must be particularly responsive. Thus, we proposed and designed a Raspberry Pi-based edge computing system to computer-intensive care unit (ICU) data at the periphery of the network to offload the hospital cloud platform. ICU medical data were simulated from the PhysioNet MIMIC III database and transferred to the edge platform for computation and identification of emergency cases that were then sent to the cloud level. We further discuss the current issues and prospects of edge computing in hospitals. © 2021 ECBIOS 2021. All rights reserved.

关键词： Intensive care units

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Cytometry in the Short-Wave Infrared

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ACS Nano 2024年第28期18卷 18534-18547页

作者： Liu, Te-I Wang, Jhih-Shan Nguyen, Ai-Phuong Raabe, Marco Quiroz Reyes, Carlos Jose Lin, Chih-Hsin Lin, Ching-Wei Institute of Atomic and Molecular Sciences Academia Sinica Taipei City106319 Taiwan Department of Materials Science and Engineering National Taiwan University Taipei City106319 Taiwan Department of Physics University of Stuttgart Stuttgart70174 Germany Department of Chemistry National Tsing Hua University Hsinchu300044 Taiwan International Ph.D. Program in Biomedical Engineering Taipei Medical University New Taipei City235603 Taiwan Graduate Institute of Nanomedicine and Medical Engineering Taipei Medical University New Taipei City235603 Taiwan

Cytometry plays a crucial role in characterizing cell properties, but its restricted optical window (400-850 nm) limits the number of stained fluorophores that can be detected simultaneously and hampers the study and utilization of short-wave infrared (SWIR;900-1700 nm) fluorophores in cells. Here we introduce two SWIR-based methods to address these limitations: SWIR flow cytometry and SWIR image cytometry. We develop a quantification protocol for deducing cellular fluorophore mass. Both systems achieve a limit of detection of ∼0.1 fg cell-1 within a 30 min experimental time frame, using individualized, high-purity (6,5) single-wall carbon nanotubes as a model fluorophore and macrophage-like RAW264.7 as a model cell line. This high-sensitivity feature reveals that low-dose (6,5) serves as an antioxidant, and cell morphology and oxidative stress dose-dependently correlate with (6,5) uptake. Our SWIR cytometry holds immediate applicability for existing SWIR fluorophores and offers a solution to the issue of spectral overlapping in conventional cytometry. © 2024 The Authors. Published by American Chemical Society.

关键词： Oxygen

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Histogram-based Res-UNet model for optical sectioning HiLo endo-microscopy

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Optics Express 2025年第6期33卷 12253-12268页

作者： Chung, Meng-Chen Chia, Yu-Hsin Vyas, Sunil Luo, Yuan Department of Biomedical Engineering National Taiwan University Taipei10051 Taiwan Institute of Medical Device and Imaging National Taiwan University Taipei10051 Taiwan YongLin Institute of Health National Taiwan University Taipei10087 Taiwan Molecular Imaging Center National Taiwan University Taipei10672 Taiwan Program for Precision Health and Intelligent Medicine National Taiwan University Taipei106319 Taiwan

Optical sectioning endo-microscopy has become a crucial tool for deep brain imaging, but conventional methods face challenges such as time-consuming scanning processes and the need for expensive light sources. HiLo imaging addresses these issues by providing faster acquisition and high-quality images. In this study, we introduce a histogram matching-based Res-UNet model for optical sectioning HiLo endo-microscopy. By applying our model, we achieve substantial improvements in image reconstruction quality compared to the conventional ResNet model. Our evaluation demonstrates significant enhancements in the reconstructed images’ structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) metrics. The PSNR values exceeding 30 dB and SSIM values surpassing 0.8 at various depths indicate that our method achieves image quality comparable to the HiLo system. Importantly, while our approach demonstrates high-quality, real-time reconstruction capabilities using ex-vivo samples, we are actively planning to extend our research to in-vivo imaging applications, which will further enhance the practical implications of our work. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Brain imaging Imaging systems In vivo imaging Light sources Structured light Tissue imaging

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Conditional Convolution of Clinical Data Embeddings for Multimodal Prostate Cancer Classification

Conditional Convolution of Clinical Data Embeddings for Mult...

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IEEE International Symposium on biomedical Imaging

作者： Jiayang Zhong Fuyao Chen Lihui Chen Dennis Shung John A. Onofrey Department of Biomedical Engineering Medical Scientist Training Program Department of Biotatistics Yale School of Public Health CT USA Yale School of Medicine CT USA Radiology & Biomedical Imaging Urology

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Accurate risk prediction for prostate cancer (PCa) in multiparametric magnetic resonance imaging (mpMRI) is essential for non-invasive diagnosis. Current deep learning approaches, such as convolutional neural networks (CNNs), show promise in predicting Gleason scores (GS) directly from imaging data, yet often overlook valuable clinical data in other data modalities. In this study, we introduce EmbedCondConv a novel multimodal GS prediction model that incorporates clinical information by conditioning CNN kernels on principal components derived from patient clinical data. We tested our models on a public dataset of 921 selected MRI scans and corresponding structured data and compared the prediction performance to baseline models. Our results demonstrate that incorporating clinical information into the model improves GS prediction accuracy with AUROC of 0.90 compared to 0.69 using imaging alone. All code used in this study is publicly available at https://***/jiayangz/EmbedCondConv.

关键词： Dimensionality reduction Convolution Magnetic resonance imaging Predictive models Data models Convolutional neural networks Clinical diagnosis Prostate cancer Kernel Principal component analysis

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Ischemic Stroke Post-treatment Prediction using Machine Learning to develop Web Application for Healthcare Centers in Thailand

Ischemic Stroke Post-treatment Prediction using Machine Lear...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Worraviseat, Kulwarin Danvirutai, Pobporn Anutrakulchai, Sirirat Kasemsap, Narongrit Srichan, Chavis Khon Kaen University Faculty of Engineering Department of Biomedical Engineering Khon Kaen Thailand Postdoctoral Research Program Khon Kaen University Khon Kaen Thailand Khan Kaen University Faculty of Medicine Department of Medicine Khon Kaen Thailand Khan Kaen University Faculty of Engineering Khon Kaen Thailand

ISBN: (纸本)9798350332360

Stroke attack is one of the most serious concerns in an emergency room. Expert diagnosis and accurate treatment are crucial for the improvement, death, or impairment of the patients. This work aims at using big data analytics for developing a system to provide the probability for each patient whether he would improve after medications. Records of N=1700 volunteers were gathered for non-linear classification training. Random Forest outperforms seven other methods compared in this study. The AI model was deployed as a web application for a rural hospital to assist medical personnel. This can be considered an important step towards AI-assisted emergency medications for stroke. Under the situation where the NIH Stroke Score was unavailable on time, the system could still provide the improvement probability via a web application based on the AI model trained in this work. © 2023 IEEE.

关键词： Diagnosis

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Title: Challenges in single cells sequencing Microbial community and biofilm: A case of Oleidesulfovibrio alaskensis G20 NGS protocol

Title: Challenges in single cells sequencing Microbial commu...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Singh, Ram Nageena Gnimpieba, Etienne Z. Sani, Rajesh Kumar Chemical and Biological Engineering South Dakota School of Mines and Technology Rapid City United States University of South Dakota Gear Center Biomedical Engineering Program Sioux Falls United States

ISBN: (纸本)9781665468190

Biofilm, is a special-complex organization of bacterial cells with multiple layers, formed in certain environmental conditions. In the complex biofilm different bacterial (single) cells perform different functions and contribute to overall biofilm activity, where single bacterial cells are in different physiological states of growth, stress and signaling. Sulphate reducing bacteria (SRB) contributes to huge economic loss ({}4B) causing microbial induced corrosion. To effectively combat the challenges posed by SRB, it is essential to understand their molecular mechanisms of biofilm formation and biocorrosion. Single Cell Genomics (single cell transcriptomics) is a technique which investigates the gene expression at the level of a single biological cell and could not be attainable in bulk analysis (RNASeq) could decipher the uniqueness of each cell in complex group. We are developing a NGS (oxford Nanopore)-workflow for single cell transcriptomics of biofilms using Oleidesulfovibrio alaskensis (earlier Desulfovibrio alaskensis) strain G20 (OA-G20) as a model. We encountered several challenges to design and develop the workflow such 1) absence of ploy(A) tail in mRNAs, 2) amount of total RNA, 3) half-lives of mRNAs, 4) perforation of cell membrane, 5) low copy number of mRNAs, 6) single cell suspension and cell sorting, 7) quantification of bacterial cells, 8) fixation of cells, 9) designing of probes, 10) hybridization of probes and 11) amplification of mRNAs. Here, we are presenting how we resolved some of these challenges to design and develop a single cell genomics (transcriptomics) workflow for SRB biofilms. © 2022 IEEE.

关键词： Genome

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Study of Cell Encapsulation System in Using Thai Silk Fibroin-Based Hydrogel

Study of Cell Encapsulation System in Using Thai Silk Fibroi...

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biomedical engineering International Conference (BMEiCON)

作者： Nitchaya Suksomthong Sasitorn Aueviriyavit Juthamas Ratanavaraporn Interdisciplinary Program of Biomedical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Nano Safety and Bioactivity Research Team National Nanotechnology Center National Science and Technology Development Agency (NSTDA) Pathum Thani Thailand Biomedical Engineering Program Biomedical Engineering Research Center Biomaterial Engineering for Medical and Health Research Unit Faculty of Engineering Chulalongkorn University Bangkok Thailand

Designing biomimetic tissue models and developing scaffolds under cell-compatible protocols are a challenge in the field of tissue engineering. Cell encapsulation technique was selected with hydrogel fabrication due to its similarity to the condition within the human body. This study proposed SF-based hydrogels with the aim of application as cell encapsulation matrix. The vital properties, including gelation, diffusion, and cell viability were evaluated. SF/DMPG hydrogels exhibited rapid gelation and sufficient diffusion. L929 cells encapsulated in SF/DMPG survived after the fabrication process, with proliferation occurred at day 1 of culture which was done in static condition. The developed hydrogels showed potential application as a cell encapsulation matrix using tissue engineering, especially bioink.

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Measurement of peripheral nerve magnetostimulation thresholds of a head solenoid coil between 200 Hz and 88.1 kHz

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IEEE Journal of Translational engineering in Health and Medicine 2025年 13卷 275-285页

作者： Barksdale, Alex C. Ferris, Natalie G. Mattingly, Eli Sliwiak, Monika Guerin, Bastien Wald, Lawrence L. Davids, Mathias Klein, Valerie MIT Department of Electrical Engineering and Computer Science CambridgeMA United States Martinos Center for Biomedical Imaging CharlestownMA United States Harvard University Harvard Graduate Program in Biophysics CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology BostonMA United States Harvard Medical School BostonMA United States

Objective: Magnetic fields switching at kilohertz frequencies induce electric fields in the body, which can cause peripheral nerve stimulation (PNS). Although magnetostimulation has been extensively studied below 10 kHz, the behavior of PNS at higher frequencies remains poorly understood. This study aims to investigate PNS thresholds at frequencies up to 88.1 kHz and to explore deviations from the widely accepted hyperbolic strength-duration curve (SDC). Methods and procedures: PNS thresholds were measured in the head of 8 human volunteers using a solenoidal coil at 16 distinct frequencies, ranging from 200 Hz to 88.1 kHz. A hyperbolic SDC was used as a reference to compare the frequency-dependent behavior of PNS thresholds. Results: Contrary to the predictions of the hyperbolic SDC, PNS thresholds did not decrease monotonically with frequency. Instead, thresholds reached a minimum near 25 kHz, after which they increased by an average of 39% from 25 kHz to 88.1 kHz across subjects. This pattern indicates a significant deviation from previously observed behavior at lower frequencies. Conclusion: Our results suggest that PNS thresholds exhibit a non-monotonic frequency dependence at higher frequencies, diverging from the traditional hyperbolic SDC. These findings offer critical data for refining neurodynamic models and provide insights for setting PNS safety limits in applications like MRI gradient coils and magnetic particle imaging (MPI). Further investigation is needed to understand the biological mechanisms driving these deviations beyond 25 kHz. Clinical impact: These findings call for further basic research into biological mechanisms underlying high frequency PNS threshold trends, and supports refinement of safety guidelines for MRI and MPI systems for clinical implementation. © 2013 IEEE.

关键词： Neuroimaging

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A dual-fluorescence assay for gene delivery vehicle screening in macrophages with an inflammation-inducible reporter construct

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BMC methods 2025年第1期2卷 8页

作者： Allie Ivy Shelby N Bess Shilpi Agrawal Varun Kochar Abbey L Stokes Timothy J Muldoon Christopher E Nelson Department of Biomedical Engineering University of Arkansas 120 John A. White Jr. Engineering Hall Fayetteville AR 72701 USA. Cell and Molecular Biology Program University of Arkansas Fayetteville AR USA.

Background:Macrophages are a promising target for therapeutics in various applications such as regenerative medicine and immunotherapy for cancer. Due to their plastic nature, macrophages can switch from a non-activated state to activated with the smallest environmental change. For macrophages to be effective in their respective applications, screening for phenotypic changes is necessary to elucidate the cell response to different delivery vehicles, vaccines, small molecules, and other stimuli. Methods:We created a sensitive and dynamic high-throughput screening method for macrophages based on the activation of NF-κB. For this reporter, we placed an mRFP1 fluorescence gene under the control of an inflammatory promoter, which recruits NF-κB response elements to promote expression during the inflammatory response in macrophages. We characterized the inflammatory reporter based on key markers of an inflammatory response in macrophages including TNF-α cytokine release and immunostaining for inflammatory and non-inflammatory cell surface markers. We compared gene delivery and inflammation of several clinically relevant viral vehicles and commercially available non-viral vehicles. Statistical analysis between groups was performed with a one-way ANOVA with post-hoc Tukey's test. Results:The reporter macrophages demonstrated a dynamic range after LPS stimulation with an EC50 of 0.61 ng/mL that was highly predictive of TNF-α release. Flow cytometry revealed heterogeneity between groups but confirmed population level shifts in pro-inflammatory markers. Finally, we demonstrated utility of the reporter by showing divergent effects with various leading gene delivery vehicles. Discussion:This screening technique developed here provides a dynamic, high-throughput screening technique for determining inflammatory response by mouse macrophages to specific stimuli. The method presented here provides insight into the inflammatory response in mouse macrophages to different viral and non

关键词： Gene delivery Inflammation Macrophage NF-κB Reporter

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Modeling of Calcium-dependent Low Intensity Low Frequency Ultrasound Modulation of a Hodgkin–Huxley Neuron

Modeling of Calcium-dependent Low Intensity Low Frequency Ul...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Heba M. Badawe Massoud L. Khraiche Neural Engineering and Nanobiosensors Group Biomedical Engineering Program Maroun Semaan Faculty of Engineering and Architecture American University of Beirut Beirut Lebanon

Non-invasive low intensity, low frequency ultrasound is a progressive neuromodulation approach that can reach deep brain areas with peak spatial and temporal resolution for highly-targeted diagnostic and therapeutic purposes. Coupling the ultrasound mechanical effects to the neural membrane comprises different mechanisms that are, to-date, still a topic of debate. The availability of calcium ions in the extracellular medium is of high significance when it comes to the effect of ultrasound on the neural tissue. Whereby the generated calcium influx can directly affect the voltage-gated ion channels, amplifying their action. We modeled the flexoelectric-induced effects of ultrasound to a single firing neuron, taking into consideration the effect of calcium channel embedding into the neural membrane on the neuron’s firing rate, latency response, peak-to-peak voltage, and general shape of the action *** Relevance— Upon Ultrasound sonication, the mechanical waves interact with the neural membrane and alter the kinetics of the calcium channels, thus changing the neural response.

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