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Ultrasound-guided drug delivery system utilizing piezocatalytic MoS2 nanomaterials for anti-inflammatory therapy

Nano Energy 2024年 127卷

作者： Lin, Ssu-Chi Joshi, Ravindra Ganguly, Anindita Barman, Snigdha Roy Pal, Arnab Kaswan, Kuldeep Liu, Kuei-Lin Nain, Amit Kao, Fu-Cheng Lin, Zong-Hong Department of Biomedical Engineering National Taiwan University Taipei10167 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu30013 Taiwan Internet of Senses Research Center National Tsing Hua University Hsinchu30013 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan Department of Materials Engineering Indian Institute of Science Karnataka Bangalore560012 India Department of Orthopaedic Surgery Chang Gung Memorial Hospital Taoyuan33305 Taiwan College of Medicine Chang Gung University Taoyuan33302 Taiwan

Traditional drug delivery systems lack the potential of controlled drug release, thereby decreasing drug utilization and release efficiency. Herein, a next generation of stimuli-responsive drug delivery platform is designed based on piezocatalytic molybdenum disulfide nanoflowers (MoS2 NFs) which can be triggered by ultrasound (US) stimulation for effective acute inflammation therapy. Under US irradiation, MoS2 NFs undergoes piezocatalysis to generate reactive oxygen species (ROS) owing to piezoelectric polarization, thus releasing loaded anti-inflammatory drug Indomethacin (IND) to the targeted inflammation site. The cumulative release of IND elevated significantly with the increase in the duration for US exposure due to the amplified ROS generation, which displayed a highly controllable nature of the as-designed drug delivery platform. For convenient applications, the IND loaded MoS2 NFs (IND@MoS2 NFs) was functionalized onto commercial dressings and their tunable in-vivo drug release performance was demonstrated in paw edema model. IND@MoS2 NFs upon US irradiation, controllably released IND into the site-specific inflamed paw which significantly inhibited 56 % of paw swelling in 6 h by suppressing the infiltration of neutrophils and expression of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α). The highly controllable drug delivery system holds great potential in facilitating personalized, user-friendly theranostic applications with improved patient outcomes. © 2024 Elsevier Ltd

关键词： Ultrasonics

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ECG heart-beat classification using multimodal image fusion

arXiv

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arXiv 2021年

作者： Ahmad, Zeeshan Tabassum, Anika Guan, Ling Khan, Naimul Department of Electrical Computer and Biomedical Engineering Ryerson University TorontoON Canada Master of Data Science program Ryerson University TorontoON Canada

In this paper, we present a novel Image Fusion Model (IFM) for ECG heart-beat classification to overcome the weaknesses of existing machine learning techniques that rely either on manual feature extraction or direct utilization of 1D raw ECG signal. At the input of IFM, we first convert the heart-beats of ECG into three different images using Gramian Angular Field (GAF), Recurrence Plot (RP) and Markov Transition Field (MTF) and then fuse these images to create a single imaging modality. We use AlexNet for feature extraction and classification and thus employ end-to-end deep learning. We perform experiments on PhysioNet's MIT-BIH dataset for five different arrhythmias in accordance with the AAMI EC57 standard and on PTB diagnostics dataset for myocardial infarction (MI) classification. We achieved an state-of-an-art results in terms of prediction accuracy, precision and recall. © 2021, CC BY.

关键词： Extraction

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Diabetes Prediction Model for Better Clarification by using Machine Learning

Diabetes Prediction Model for Better Clarification by using ...

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International Conference on Inventive Computation Technologies (ICICT)

作者： J. Lysa Eben R. Jayasudha S. Ramya S. Kaliappan Shobha Aswal Khalid Ali Salem Al-Salehi Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Chennai Tamilnadu India Department of Mathematics Dr.N.G.P.Institute of Technology Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Erode Tamilnadu India Division of Research and Development Lovely Professional University Phagwara Punjab India School of Computing Graphic Era Hill University Dehradun India Biomedical engineering study program faculty of science and technology Airlangga University Surabaya Indonesia

Diabetes mellitus is one of the most pressing health concerns because so many people are afflicted by its disabling symptoms. Factors such as age, excess body fat, insufficient physical activity, a history of diabetes in one's family, a sedentary lifestyle, an unhealthy diet, hypertension, etc., all increase the likelihood of developing diabetes mellitus. Health complications are more common in people with diabetes, including cardiovascular disease, renal failure, stroke, blindness, and nerve injury. To validate a diagnosis of diabetes, hospitals typically perform a battery of procedures on the patient. Big data analytics has many vital applications in the healthcare sector. Numerous large computer systems are used in the healthcare sector. With the help of big data analytics, researchers can sift through mountains of data in search of previously unseen patterns and insights. Current techniques have a poor degree of precision in classification and forecast. While previous research has focused on factors such as glucose, body mass index, age, insulin, etc., the proposed model takes these into account and also the other factors that may be more relevant to the development of diabetes. The newer sample is superior to the older one based on categorization accuracy. A workflow algorithm for diabetes prognosis is also required to improve the accuracy.

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Label-Free and Liquid State Sers Detection of Multi-Scaled Bioanalytes Via Light-Induced Pinpoint Colloidal Assembly

SSRN

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SSRN 2024年

作者： Han, Seungyeon Park, Junhee Moon, Sunghyun Eom, Seonghyeon Jin, Chang Min Kim, Seungmin Ryu, Yong-Sang Choi, Yeonho Lee, Jong Bum Choi, Inhee Department of Life Science University of Seoul Seoul02504 Korea Republic of Department of Chemical Engineering University of Seoul Seoul02504 Korea Republic of Department of Biomedical Engineering Korea University Seoul02481 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02481 Korea Republic of Exopert Corporation Seoul02580 Korea Republic of Department of Applied Chemistry University of Seoul Seoul02504 Korea Republic of

Surface-enhanced Raman scattering (SERS) has been extensively applied to detect complex analytes due to its ability to enhance the fingerprint signals of molecules around nanostructured metallic surfaces. Thus, it is essential to design SERS-active nanostructures with abundant electromagnetic hotspots in a probed volume according to the dimensions of the analytes, as the analytes must be located in their hotspots for maximum signal enhancement. Herein, we demonstrate a simple method for detecting robust SERS signals from multi-scaled bioanalytes, regardless of their dimensions in the liquid state, through a photothermally driven co-assembly with colloidal plasmonic nanoparticles as signal enhancers. Under resonant light illumination, plasmonic nanoparticles and analytes in the solution quickly assemble at the focused surface area by convective movements induced by the photothermal heating of the plasmonic nanoparticles without any surface modification. Such collective assemblies of plasmonic nanoparticles and analytes were optimized by varying the optical density and surface charge of the nanoparticles, the viscosity of the solvent, and the light illumination time to maximize the SERS signals. Using these light-induced co-assemblies, the intrinsic SERS signals of small biomolecules can be detected down to nanomolar concentrations based on their fingerprint spectra. Furthermore, large-sized biomarkers, such as viruses and exosomes, were successfully detected without labels, and the complexity of the collected spectra was statistically analyzed using t-distributed stochastic neighbor embedding combined with support vector machine (t-SNE+SVM). The proposed method is expected to provide a robust and convenient method to sensitively detect biologically and environmentally relevant analytes at multiple scales in liquid samples. © 2024, The Authors. All rights reserved.

关键词： Viruses

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Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 303-314页

作者： Jia Ying Renee Cattell Tianyun Zhao Lan Lei Zhao Jiang Shahid M.Hussain Yi Gao H‑H.Sherry Chow Alison T.Stopeck Patricia A.Thompson Chuan Huang Department of Biomedical Engineering Stony Brook UniversityStony BrookNY 11794USA Department of Radiation Oncology Renaissance School of MedicineStony Brook UniversityStony BrookNY 11794USA Department of Medicine Northside Hospital GwinnettLawrencevilleGA 30046USA Program of Public Health Renaissance School of MedicineStony Brook UniversityStony BrookNY 11794USA Department of Radiology Renaissance School of MedicineStony Brook UniversityStony BrookNY 11794USA Department of Biomedical Informatics Renaissance School of MedicineStony Brook UniversityStony BrookNY 11794USA School of Biomedical Engineering Health Science CenterShenzhen UniversityShenzhen 518060China University of Arizona Cancer Center TucsonAZ 85719USA Department of Medicine Renaissance School of MedicineStony Brook UniversityStony BrookNY 11794USA Stony Brook Cancer Center Stony Brook UniversityStony BrookNY 11794USA Department of Medicine Cedar Sinai CancerCedars Sinai Medical CenterLos AngelesCA 90048USA

Presence of higher breast density(BD)and persistence over time are risk factors for breast cancer.A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-breast segmentation is *** this study,we aimed to develop a highly reproducible and accurate whole-breast segmentation algorithm for the generation of reproducible BD *** datasets of volunteers from two clinical trials were *** MR images were acquired on 3T Siemens Biograph mMR,Prisma,and Skyra using 3D Cartesian six-echo GRE sequences with a fat-water separation *** whole-breast segmentation strategies,utiliz-ing image registration and 3D U-Net,were *** segmentation was performed.A task-based analysis was performed:a previously developed MR-based BD measure,MagDensity,was calculated and assessed using automated and manual *** mean squared error(MSE)and intraclass correlation coefficient(ICC)between MagDensity were evaluated using the manual segmentation as a *** test-retest reproducibility of MagDensity derived from different breast segmentation methods was assessed using the difference between the test and retest measures(Δ_(2-1)),MSE,and *** results showed that MagDensity derived by the registration and deep learning segmentation methods exhibited high concordance with manual segmentation,with ICCs of 0.986(95%CI:0.974-0.993)and 0.983(95%CI:0.961-0.992),*** test-retest analysis,MagDensity derived using the regis-tration algorithm achieved the smallest MSE of 0.370 and highest ICC of 0.993(95%CI:0.982-0.997)when compared to other segmentation *** conclusion,the proposed registration and deep learning whole-breast segmentation methods are accurate and reliable for estimating *** methods outperformed a previously developed algorithm and manual segmentation in the test-retest assessment,with the registration exhibiting superior performance for highly reproducibl

关键词： Breast cancer Breast density Breast segmentation Image registration Deep learning

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Fabrication of sandwich-structured capacitor containing core@shell polystyrene@graphene oxide microspheres for switchable removal of dyes from water by dielectrophoresis force

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Separation and Purification Technology 2024年 331卷

作者： Chen, Wei-Liang Cheng, Chih-Chia Lu, Chien-Hsing Chen, Jem-Kun Department of Materials Science and Engineering National Taiwan University of Science and Technology 43 Sec. 4 Keelung Road Taipei 106 Taiwan Division of Gastroenterology and Hepatology Department of Internal Medicine Chung Shan Medical University Hospital Taichung City402 Taiwan Graduate Institute of Applied Science and Technology National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Obstetrics and Gynecology Taichung Veterans General Hospital Taichung40705 Taiwan Institute of Biomedical Sciences Ph.D. Program in Translational Medicine and Rong-Hsing Research Center for Translational Medicine National Chung-Hsing University Taichung940227 Taiwan

Absorption rates for traditional adsorbents were predominately determined by the concentration gradient from bulk to absorbents and surface area. A novel sandwich-structured capacitor (SSC) containing adsorbents is designed to reduce the time consuming of absorption of pollutants by dielectrophoresis force (FDEP). Graphene oxide (GO) are coated on polystyrene microspheres (PSs) as the core/shell PS@GO adsorbents that were encapsulated within the SSC to treat the solution of dye-emulsified micells (DEM). The FDEP results the assembling of PS@GOs and DEMs under polarization and enhance the adsorption rate ca. 1 ∼ 2 times with polarization at 3 V and 200 kHz. Additionally, most adsorbents are recycled with secondary pollution. Only two-fifth pure water volume of the wastewater through the SSC could achieve the recycling of the adsorbents at 900 kHz. The high complex permittivity of GO coating at high frequency allows ultrafast alternative spinning of the induced dipoles in the PS@GOs facilitates desorption and hinders the re-adsorption of the DEM during the recycling of PS@GOs. The PS@GOs was reused ca. 10 times at 20 mL min−1 of flow rate through the SSC without damages between 200 and 900 kHz. The designed SSC containing PS@GOs accomplishes either reusing of adsorbents or concentrating of dyes with low secondary pollution in practice through frequency manipulation. © 2023 Elsevier B.V.

关键词： Graphene

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Assessment of cell death using dynamic light scattering with M-mode optical coherence tomography imaging 10

Assessment of cell death using dynamic light scattering with...

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biomedical Applications of Light Scattering X 2020

作者： Rija, Sehar Kolios, Michael C. Graduate Program of Biomedical Engineering Ryerson University Toronto Canada St. Michael's Hospital Toronto Canada Keenan Research Centre for Biomedical Science St. Michael's Hospital Toronto Canada

ISBN: (纸本)9781510632691

Optical Coherence tomography (OCT) is a rapidly developing light based imaging modality that can provide functional information and visualization of tissue morphology and cell death by quantifying the motion of intracellular structures. In this work, Dynamic light scattering (DLS) with OCT, is used to compute the time-dependent fluctuations in scattered light intensity. Using the DLS-OCT method, we have previously shown a higher rate of intracellular motion detected in apoptotic cells compared to viable cells. In this study, we aim to probe the intracellular motion of cells at much higher scan-rates that we have attempted previously to detect sub-cellular motion with greater sensitivity. To validate the DLS-OCT approach, M-mode OCT images were acquired using Thorlabs SS-OCT system (sampling rate of 100 kHz) to measure the Brownian motion in monodisperse microsphere suspensions. The results demonstrate that ACF decays more rapidly for smaller size microspheres and the experimental decorrelation time values matched with the theoretical values calculated using the Einstein-Stokes equation. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Cell death

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The Pull of Tissue engineering: A STEM Outreach program with a Modular Cyclic Stretch Device to Engage High School Students

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biomedical engineering Education 2021年第1期2卷 31-39页

作者： Ozdemir, Tugba Senocak, Erdal Gerber, Gene Tayhan, Secil Erden Brown, Justin L. Biomedical Engineering Program Chemical and Biological Engineering Department South Dakota School of Mines and Technology Rapid City USA Department of Science Education Tokat Gaziosmanpasa University Tokat Turkey Department of Biomedical Engineering The Pennsylvania State University State College USA Department of Genetics and Bioengineering Tokat Gaziosmanpasa University Tokat Turkey

In this paper we designed a STEM outreach program with a modular tissue engineering education tool (we refer to as “modular cyclic-stretch device”) to engage high school students in STEM hands-on activities. Using simple machines such as gears and rotating cams, students were able to build a custom device to apply cyclic stretch to biomaterials. With the help of this hands-on activity, our outreach program helped students grasp tendon tissue biomechanics and understand the importance of applying biomechanical force to regenerate tendon tissue in a laboratory setting. The two-day outreach program comprised: 1. pre- and post-tests; 2. lectures; 3. laboratory sessions, including the microscopic examination of stained tissue sections and a hands-on group activity employing the modular cyclic-stretch device; and 4. homework. Assessment results suggest that our program supports improved student awareness and interest in tissue engineering as a future profession. The program elevated students’ confidence in their ability to apply engineering principles to tasks such as building a modular cyclic-stretch device and measuring the mechanical properties of biological tissues. Building an educational bioreactor improved students’ understanding of the dynamic nature of the human body and the importance of tissue engineering as an emerging discipline towards replacing or regenerating damaged organs. We propose that our modular device has great outreach potential to introduce tissue engineering concepts to high school and potentially college freshmen engineering students.

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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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