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Polyelectrolyte-coated liposomes microfluidically assembled in one-step for enhancing cell endocytosis and in-vivo immune responses

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Colloids and Surfaces B: Biointerfaces 2024年 241卷 114030页

作者： Chen, Xin-an Chuang, Chuan-chang Chen, Cheng-cheung Lee, Chia-ying Chin, Chia-ying Young, Jenn-jong Bai, Meng-yi Chuang, Chuan-chung Biomedical Engineering Program Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei City10607 Taiwan Institute of Preventive Medicine National Defense Medical Center New Taipei City23742 Taiwan Department and Graduate Institute of Microbiology and Immunology National Defense Medical Center Taipei City11490 Taiwan Graduate Institute of Medical Sciences National Defense Medical Center Taipei City11490 Taiwan Adjunct Appointment to the Department of Biomedical Engineering National Defense Medical Center Taipei City11490 Taiwan School of Dentistry and Graduate Institute of Dental Science National Defense Medical Center Taipei City11490 Taiwan Department of dentistry Tri-Service General Hospital Taipei City11490 Taiwan

To enhance the cellular uptake of liposomes, we prepared conventional liposomes with targeting molecules and surface-charged liposomes and evaluated their potential as nano-carriers and vaccine adjuvants by comparing their endocytosis efficiencies using immune cells. Surface-charged liposomes were synthesized via a one-step microfluidic method, which provided a novel, simple, fast, and highly reproducible method for preparing liposomes. Flow cytometry revealed that cationic polyelectrolyte-coated liposomes exhibited higher endocytosis efficiencies (of up to a factor of 100) in A774A.1 cells and JAWs II cells compared with uncoated liposomes or those coated with anionic polyelectrolytes. Positively charged liposomes exhibited some cytotoxicity at quaternary-chitosan coating concentrations higher than 6 mg/mL;however, significantly lower cytotoxicities (by a factor of almost ten) were obtained by protein mixing. Furthermore, BALB/c mice vaccinated with a mixture of Anthrax vaccine adsorbed (AVA) and quaternary chitosan-coated liposomes showed faster and stronger anti-PA IgG inductions compared to those vaccinated with AVA alone, with titers positively correlating with the amount of cationic liposome used. This finding clearly reveals that quaternary chitosan-coated liposomes act as both nano-carriers and vaccine adjuvants that significantly enhance in-vivo immune responses to vaccines with low immunogenicities. © 2024 Elsevier B.V.

关键词： Polyelectrolytes

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Wearable strain sensor utilizing the synergistic effect of Ti3C2Tx MXene/AgNW nanohybrid for point-of-care respiratory monitoring

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Materials Today Chemistry 2024年 37卷

作者： Kumar, Amit Kumar, R.K. Rakesh Shaikh, Muhammad Omar Yang, Jia-Yu Bharti, Aditya Manu Huang, Bo-Yan Chang, Hsu-Liang Lee, Da-Huei Chuang, Cheng-Hsin Institute of Medical Science and Technology National Sun Yat-sen University Kaohsiung80424 Taiwan Department of Chemical Engineering National Taiwan University Taipei City10617 Taiwan Institute of Biomedical Engineering and Nanomedicine National Healthcare Research Institutes 350 Miaoli County Taiwan National Sun Yat-sen University Kaohsiung80424 Taiwan Sustainability Science and Engineering Program Tunghai University Taichung407224 Taiwan Department of Internal Medicine Kaohsiung Municipal Ta-Tung Hospital Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Department of Electrical Engineering National Chung-Kung University Tainan Taiwan

Respiratory signals are significant indicators for detecting changes in physiological conditions and early diagnosis of numerous respiratory illnesses. Herein, we have integrated a high-performance strain sensor and portable circuit board (PCB) with personalized interface to develop point-of-care respiratory monitoring device. The ultrasensitive strain sensor utilizes a conductive polymeric nanocomposite that harnesses the synergistic effect of Ti3C2Tx (MXene)/AgNW nanohybrid to develop a wearable device. The wearable device is capable of analysing pulmonary volumes, such as forced volume capacity (FVC) and forced expiratory volume (FEV1), while accurately recognizing various breathing patterns in a resting state (such as normal, forced, and obstructive), as well as during different physical activities. It shows excellent correlation (>93%) with commercial spirometer for measurement of pulmonary parameters. In addition, we present a wireless device for lab rat respiratory monitoring in anaesthetic state. The device is implemented for real-time respiratory monitoring under mild, normal and high anaesthesia doses. The levels of anaesthesia doses including a critical limit can be significantly discriminated by means of breathing frequency and amplitude, which ultimately results in saving their lives. These results demonstrate the practical feasibility of the strain sensing device as wearable electronics for point-of-care respiratory monitoring in humans and other species. © 2024 Elsevier Ltd

关键词： Diagnosis

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A digital microfluidic device integrated with electrochemical sensor and 3D matrix for detecting soluble PD-L1

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Biosensors and Bioelectronics: X 2024年 19卷 100490页

作者： Zhang, Yuqian Liu, Jing Lo, Ting-Wen Kim, Yohan Lucien, Fabrice Dong, Haidong Liu, Yuguang Department of Physiology & Biomedical Engineering Mayo Clinic RochesterMN55905 United States Microbiomics Program Center for Individualized Medicine Mayo Clinic RochesterMN55905 United States Department of Urology Mayo Clinic College of Medicine and Science RochesterMN55905 United States Department of Immunology Mayo Clinic RochesterMN55905 United States Department of Surgery Mayo Clinic RochesterMN55905 United States

PD1/PD-L1 checkpoint inhibitors are at the forefront of cancer immunotherapies. However, the overall response rate remains only 10–30%. Even among initial responders, drug resistance often occurs, which can lead to prolonged use of a futile therapy in the race with the fatal disease. It would be ideal to closely monitor key indicators of patients’ immune responsiveness, such as circulating PD-L1 levels. Traditional PD-L1 detection methods, such as ELISA, are limited in sensitivity and rely on core lab facilities, preventing their use for the regular monitoring. Electrochemical sensors exist as an attractive candidate for point-of-care tool, yet, streamlining multiple processes in a single platform remains a challenge. To overcome this challenge, this work integrated electrochemical sensor arrays into a digital microfluidic device to combine their distinct merits, so that soluble PD-L1 (sPD-L1) molecules can be rapidly detected in a programmed and automated manner. This new platform featured microscale electrochemical sensor arrays modified with electrically conductive 3D matrix, and can detect as low as 1 pg/mL sPD-L1 with high specificity. The sensors also have desired repeatability and can obtain reproducible results on different days. To demonstrate the functionality of the device to process more complex biofluids, we used the device to detect sPD-L1 molecules secreted by human breast cancer cell line in culture media directly and observed 2X increase in signal compared with control experiment. This novel platform holds promise for the close monitoring of sPD-L1 level in human physiological fluids to evaluate the efficacy of PD-1/PD-L1 immunotherapy. © 2024 The Author(s)

关键词： Digital microfluidics

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High performance gamma-ray spectrometer based on Cs3Cu2I5 single crystal grown by room-temperature vacuum solvent-evaporation method

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Journal of Alloys and Compounds 2025年 1027卷

作者： Seo, Jiwon Song, Seungho Park, Minhwan Byun, Jangwon Park, Beomjun Park, Chansun Jang, Mee Yeom, Jung-Yeol Dept. of Health and Safety Convergence Science Korea University Seoul02841 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02841 Korea Republic of Dept. of Bioengineering Korea University Seoul02841 Korea Republic of Dept. of Materials Science and Engineering Korea University Seoul02841 Korea Republic of The Institute for High Technology Materials and Devices Korea University Seoul02841 Korea Republic of Global Health Technology Center Korea University Seoul02841 Korea Republic of Daejeon34057 Korea Republic of School of Biomedical Engineering Korea University Seoul02841 Korea Republic of

In this study, the properties of Cs3Cu2I5 (CCI) crystals grown using the Slow Vacuum Evaporation Technique (SVET) were examined. Crystals were grown at room temperature (300 K, 27 °C) under vacuum conditions, producing single crystals with maximum diameter of 13 mm over 23 days. We confirmed excellent crystallinity via X-ray diffraction (XRD), compositional uniformity via X-ray photoelectron spectroscopy (XPS), and homogeneity via electron probe micro analyzer (EPMA). UV-Vis measurements indicated a high transmittance of 83 % and a bandgap of 3.64 eV. The Stokes shift of 110 nm, smaller than previously reported values, contributed to faster decay times and improved low-energy detection feasibility. Time-resolved photoluminescence (TR-PL) showed a rapid decay component (4.1 ns), accounting for 95.11 % of the total decay, demonstrating superior properties compared to existing reports. The gamma-ray detection capabilities of the CCI crystals were evaluated using six radioactive sources (Am-241, Ba-133, Co-57, Na-22, Cs-137, and Mn-54), achieving excellent energy resolution, including 5.2 % at 662 keV. The crystals displayed a highly linear response to gamma radiation (R² = 0.99998) with a light yield of 55,613 photons/MeV. Moreover, assessments of multiple crystals grown under identical conditions showed consistent performance with a coefficient of variation (CV) of 1.23 %. These findings confirm that SVET is a highly effective and cost-efficient method for producing high-quality CCI crystals, offering significant advantages over other growth techniques. © 2025 Elsevier B.V.

关键词： Gamma ray spectrometers

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Ogden Material Calibration via Magnetic Resonance Cartography, Parameter Sensitivity, and Variational System Identification

arXiv

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arXiv 2022年

作者： Nikolov, Denislav P. Srivastava, Siddhartha Abeid, Bachir A. Scheven, Ulrich M. Arruda, Ellen M. Garikipati, Krishna Estrada, Jonathan B. Department of Mechanical Engineering University of Michigan United States Department of Biomedical Engineering University of Michigan United States Program in Macromolecular Science and Engineering University of Michigan United States Department of Mathematics University of Michigan United States Michigan Institute for Computational Discovery and Eng. University of Michigan United States

Contemporary material characterisation techniques that leverage deformation fields and the weak form of the equilibrium equations face challenges in the numerical solution procedure of the inverse characterisation problem. As material models and descriptions differ, so too must the approaches for identifying parameters and their corresponding mechanisms. The widely-used Ogden material model can be comprised of a chosen number of terms of the same mathematical form, which presents challenges of parsimonious representation, interpretability, and stability. Robust techniques for system identification of any material model are important to assess and improve experimental design, in addition to their centrality to forward computations. Using fully 3D displacement fields acquired in silicone elastomers with our recently-developed magnetic resonance cartography (MR-u) technique on the order of > 20, 000 points per sample, we leverage PDE-constrained optimisation as the basis of variational system identification of our material parameters. We incorporate the statistical F-test to maintain parsimony of representation. Using a new, local deformation decomposition locally into mixtures of biaxial and uniaxial tensile states, we evaluate experiments based on an analytical sensitivity metric, and discuss the implications for experimental design. © 2022, CC BY-NC-ND.

关键词： Inverse problems

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Spatial Distribution of Reduced Density of Hard Spheres Near a Hard-Sphere Dimer: Results from Three-Dimensional Ornstein–Zernike Equations Coupled with Several Different Closures and from Grand Canonical Monte Carlo Simulation

SSRN

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SSRN 2023年

作者： Matsuo, Mika Nakamura, Yuka Kinoshita, Masahiro Akiyama, Ryo Department of Chemistry Kyushu University Fukuoka819-0395 Japan Interdisciplinary Program of Biomedical Engineering Assistive Technology and Art and Sports Sciences Faculty of Engineering Niigata University Niigata950-2181 Japan Department of Chemistry Graduate School of Science Chiba University Chiba263-8522 Japan Center for the Promotion of Interdisciplinary Education and Research Kyoto University Kyoto606-8501 Japan

We calculated the spatial distribution of the reduced density and pair distribution function (PDF) of solvent hard spheres near a solute using three-dimensional Ornstein–Zernike (OZ) equations coupled with closures in which Percus–Yevick (PY) and hypernetted–chain (HNC) approximations were used or in which the bridge functions (BFs)proposed by Verlet, Duh and Henderson, and Kinoshita were incorporated. The solute was formed by two solvent hard spheres in contact with each other, with the result that the system was not radial-symmetric, necessitating the extension of the Verlet, Duh–Henderson, and Kinoshita BFs to three-variable functions considered in the Cartesian coordinate system. The results were compared with those from grand canonical Monte Carlo (MC) simulations. In terms of the PDF, HNC was superior to PY in the sense that the results from the former are closer to those from MC. Incorporation of the three BFs made the results even closer to those from MC. The three BFs shared almost the sameperformance for a solute immersed in a one-component solvent at the infinite-dilution limit. Analyses on the triplet distribution function (TDF) were also performed. It was found that in terms of the TDF, the incorporation of the BFs does not necessarily lead to improvement. © 2023, The Authors. All rights reserved.

关键词： Distribution functions

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Interpretable ECG Analysis for Myocardial Infarction Detection through Counterfactuals

arXiv

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arXiv 2023年

作者： Tanyel, Toygar Atmaca, Sezgin Gökçe, Kaan Balık, M. Yiğit Güler, Arda Aslanger, Emre Öksüz, İlkay Biomedical Engineering Graduate Program Istanbul Technical University Istanbul Turkey Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital Istanbul Turkey Department of Computer Science Aalto University Espoo Finland Department of Cardiology Başakşehir Pine and Sakura City Hospital Istanbul Turkey Department of Computer Engineering Istanbul Technical University Istanbul Turkey

In the evolving landscape of ECG signal analysis, the challenge of limited transparency in machine learning models remains a significant barrier to their effective integration into clinical practice. This study addresses this issue by investigating the use of counterfactual explanations to improve model interpretability for clinicians, particularly in differentiating healthy subjects from myocardial infarction patients. Utilizing the PTB-XL dataset, we developed a methodology for systematic feature extraction and refinement to prepare for counterfactual analysis. This led to the creation of the Visualizing Counterfactual Clues on Electrocardiograms (VCCE) method, designed to improve the practicality of counterfactual explanations in a clinical setting. The validity of our approach was assessed using custom metrics that reflect the diagnostic relevance of counterfactuals, evaluated with the help of two cardiologists. Our findings suggest that this approach could support future efforts in using ECGs to predict patient outcomes for cardiac conditions, achieving interpretation validity scores of 23.29 ± 1.04 and 20.28 ± 0.99 out of 25 for high and moderate-quality interpretations, respectively. Clinical alignment scores of 0.83 ± 0.12 for high-quality and 0.57 ± 0.10 for moderate-quality interpretations underscore the potential clinical applicability of our method. The methodology and findings of this study contribute to the ongoing discussion on enhancing the interpretability of machine learning models in cardiology, offering a concept that bridges the gap between advanced data analysis techniques and clinical decision-making. The source code for this study is available at https://***/tanyelai/vcce. © 2023, CC BY-NC-SA.

关键词： Contrastive Learning

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BPS2025 - A DNA tensiometer for studying load-dependent detachment kinetics of kinesins 1, 2, and 3

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Biophysical Journal 2025年第3期124卷 473a-474a页

作者： Crystal R. Noell Tzu-Chen Ma Scott McKinley William O. Hancock Biomedical Sciences Program Pennsylvania State University University Park PA USA School of Science and Engineering Tulane University New Orleans LA USA

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The biocompatibility and hemostatic efficacy of silk fibroin nanofibrils fabricated by Shear-Induced phase separation process

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Chemical engineering Journal 2023年 474卷

作者： Lu, Po-Wen Wu, Yu-Tzu Chang, Liang-Yu Lu, Tzu-Wei Jaihao, Chonlachat Huang, Ching-Shuan Murphy Chuang, Mo-Fei Lin, Chunche Chen, Innie Brangule, Agnese Zarkov, Aleksej Kareiva, Aivaras Yang, Jen-Chang Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11052 Taiwan Division of Gastroenterology and Hepatology Department of Internal Medicine Shuang Ho Hospital Taipei Medical University Zhongzheng Rd. Taipei Zhonghe23561 Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University 250 Wu-Hsing Street Taipei11031 Taiwan Department of Dentistry Taipei Medical University Hospital Taipei11031 Taiwan Institute of Organic and Polymeric Materials National Taipei University of Technology Taipei106344 Taiwan Research and Development Center for Smart Textile Technology National Taipei University of Technology Taipei106344 Taiwan Innie Chen Department of Obstetrics and Gynecology University of Ottawa OttawaONK1H 7W9 Canada Department of Pharmaceutical Chemistry Riga Stradins University RīgaLV-1007 Latvia Institute of Chemistry Vilnius University Naugarduko 24 VilniusLT-03225 Lithuania International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device Taipei Medical University Taipei11031 Taiwan Research Center of Digital Oral Science and Technology Taipei Medical University Taipei11031 Taiwan

The objectives of this study were to investigate the biocompatibility and hemostatic efficacy of silk fibroin nanofibrils (SFNFs). Unlike a conventional dialysis/freeze-drying process, SFNFs were prepared using a novel shear-induced phase-separation method. The morphology, particle size distribution, protein secondary structures, and crystalline structures of the resulting SFNFs were respectively investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), laser diffraction (LD), Fourier-transform infrared (FTIR) spectroscopy, and x-ray diffraction (XRD) deconvolution analyses. Polar and non-polar extractants of SFNFs under a bath ratio of 0.2 g/mL were collected after individually soaking them into 0.9% normal saline and cottonseed oil. In vitro hemolysis ratios, biocompatibility, and sensitization tests were carried out. Then, the hemostatic efficacy was assayed using a rat liver punch biopsy model. Compared to dialyzed/freeze-dried SF, the harvested SFNFs revealed high surface area in morphology. The median particle size distribution, D50, was 294 μm for SFNFs. Shear-induced hydrogen bonding, crystallization, and phase separation tended to give the SFNFs a high crystalline index (CI) and degree of crystallinity (DC). The hemolysis ratio of SFNFs was 0.86 ± 0.40%, and it was classified as being non-hemolytic (0%∼2%). The test results of toxicity and skin sensitization were both negative. The hemostasis time for SFNFs (2.8 ± 0.6 min) was statistically less than that of oxidized cellulose (4.3 ± 0.9 min) (p © 2023 Elsevier B.V.

关键词： Biocompatibility

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Deep Learning Approach to Modeling and Exploring Random Sources of Gate-All-Around Silicon Nanosheet MOSFETs

Deep Learning Approach to Modeling and Exploring Random Sour...

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2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang-Ming Chiao Tung University Parallel and Scientific Computing Laboratory Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Electrical Engineering and Computer Science International Graduate Program Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Communications Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Department of Electrical Engineering and Computer Engineering Hsinchu300 Taiwan National Yang-Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300 Taiwan Center for mmWave Smart Radar System and Technologies National Yang-Ming Chiao Tung University 1001 Ta-Hsueh Rd. Hsinchu300 Taiwan

ISBN: (纸本)9781665409230

In this paper, for the first time, deep learning (DL) based artificial neural network (ANN) is applied to model the effects of various random variations: work function fluctuation, random dopant fluctuation, and interface trap fluctuation, on gate-all-around silicon nanosheet MOSFETs. The number of fluctuations for each source variation is used as input features and their effects on devices of interest are studied qualitatively and quantitatively. The key figures of merit (FoM) are also extracted accurately from the transfer characteristics, which shows the competency of the ANN model in the domain of device modeling. © 2022 IEEE.

关键词： Nanosheets

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