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3D printed bioactive composite scaffolds for bone tissue engineering

Bioprinting 2020年 17卷

作者： Moukbil, Yunis Isindag, Busra Gayir, Velican Ozbek, Burak Haskoylu, Merve Erginer Oner, Ebru Toksoy Oktar, Faik Nuzhet Ikram, Fakhera Sengor, Mustafa Gunduz, Oguzhan Department of Bioengineering Faculty of Engineering Marmara University Istanbul Turkey Center for Nanotechnology & Biomaterials Application and Research Marmara University Istanbul 34722 Turkey Institute of Pure and Applied Sciences Metallurgical and Materials Engineering Marmara University Istanbul Turkey Industrial Biotechnology and System Biology Laboratory Department of Bioengineering Marmara University Istanbul Turkey Interdisciplinary Research Centre in Biomedical Materials COMSATS University Islamabad Lahore Campus Defence Road Off Raiwind Road Lahore 54000 Pakistan Department of Mechanical Engineering Faculty of Engineering Bogazici University Bebek Istanbul 34342 Turkey Department of Metallurgical and Materials Engineering Faculty of Technology Marmara University Istanbul Turkey

Bone health and regeneration is crucial to human survival. With the advancement in the bone research area, bone implants have been under scrutiny to find a better material that could help in bone regeneration and growth. A wide range of material has been studied and examined to find the ideal combination. In this paper, a new blend of Tri-calcium phosphate (TCP), polycaprolactone (PCL) and bovine hydroxyapatite (BHA) was introduced to create scaffolds with fused deposition 3d printing. Effect of BHA concentration as a naturally derived and newcomer 3d printing material was investigated via FTIR, XRD, and SEM analyses. In vitro studies were exhibited that 15% (wt/wt) BHA fabricated composite scaffolds possessed more bioactivity than other cases with increasing proliferation and growth rates. © 2019 Elsevier B.V.

关键词： 3D printing Bone scaffold Calcium phosphate Hydroxyapatite Polycaprolactone

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Corrigendum to "Mathematical model of modified hybrid pump mechanism for cardiopulmonary resuscitation" [Computer methods and programs in biomedicine 206 (2021) 106106]

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Computer methods and programs in biomedicine 2022年 218卷 106711页

作者： Dong Ah Shin Jung Chan Lee Interdisciplinary Program in Bioengineering Graduate School Seoul National University Seoul 08826 Republic of Korea. Department of Biomedical Engineering College of Medicine and Institute of Medical and Biological Engineering Medical Research Center Seoul National University Seoul 03080 Republic of Korea Institute of BioEngineering Bio-MAX Institute Seoul National University Seoul 08826 Republic of Korea. Electronic address: ljch@snu.ac.kr.

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Blood absorption improvement of a naturally derived hemostatic agent by atmospheric pressure plasma jet

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Materials Today: Proceedings 2019年 17卷 2088-2096页

作者： Jureeporn Jaifu Kittiya Thunsiri Suruk Udomsom Dheerawan Boonyawan Wassanai Wattanutchariya Biomedical engineering program Faculty of Engineering Chiang Mai University Chaing Mai Thailand Biomedical engineering center(BMEC) Chiang Mai University Chiang Mai 50200 Thailand Advanced manufacturing technology research center(AMTech) Department of Industrial Engineering Chiang Mai University Chiang Mai Thailand Plasma and beam physics research facility(PBP) Department of Physics and Materials Faculty of Science Chiang Mai University Chiang Mai Thailand

Hemostatic capability improvement of a chitosan hemostatic agent was achieved by surface modification using the atmospheric pressure plasma jet experiment. The chitosan hemostatic agent acquired high blood absorption rate, at 4.60 ml/m, when exposed to input power 10 W of the radiofrequency power supply, the argon flow rate of 4 L/m mixture with an oxygen gas of 10 ml/m, and treatment time of 30 s. A significant decreased was observed in the hemoglobin leak value, inducing early blood clotting ability of clotting in 30 s. The strong relation of gas plasma discharge with the OH radical and the atomic oxygen, exhibited an increase in the hydrophilic properties, which lead to the chitosan hemostatic agent being very effective.

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SEX DIFFERENCES IN THE DENDRITIC MORPHOLOGY OF TEMPORAL CORTICAL NEURONS IN ADULT MICE

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IBRO Neuroscience Reports 2023年 15卷 S245-S245页

作者： Mariana Pais Joana Gonçalves João Martins Miguel Castelo-Branco Luísa Pinto Inês Ribeiro University of Coimbra Faculty Of Sciences And Technology Doctoral Program In Biomedical Engineering Coimbra Portugal University of Coimbra Coimbra Institute For Biomedical Imaging And Translational Research (cibit) Coimbra Portugal ICNAS Universidade de Coimbra Pólo Das Ciências Da Saúde Coimbra Portugal Faculty of Medicine (FMUC) University Of Coimbra Coimbra Portugal University of Minho Life And Health Sciences Research Institute (icvs) School Of Medicine Braga Portugal University of Minho Icvs/3b’s - Pt Government Associate Laborator Braga Portugal

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Different Particle Sizes of Momordica Charantia Leaf Powder Modify the Rheological and Textural Properties of Corn Starch-Based 3d Food Printing Ink

SSRN

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SSRN 2023年

作者： Fan, Meiqi Choi, Young-Jin Wedamulla, Nishala Erandi Oh, Mirae Bae, Sung Mun Yang, Daeun Kang, Hyo Tang, Yujiao Moon, Sang-Ho Kim, Eun-Kyung Division of Food Bioscience College of Biomedical and Health Sciences Konkuk University Chungju27478 Korea Republic of Department of Food Science and Nutrition College of Health Science Dong-A University Busan49315 Korea Republic of Department of Health Sciences The Graduate School of Dong-A University Busan49315 Korea Republic of Department of Food Science and Technology Faculty of Animal Science and Export Agriculture Uva Wellassa University Badulla90000 Sri Lanka Grassland and Forages Division National Institute of Animal Science Rural Development Administration Cheonan31000 Korea Republic of Gyeongnam Agricultural Research and Extension Services Jinju52733 Korea Republic of BK-21 Four Graduate Program Department of Chemical Engineering Dong-A University Busan49315 Korea Republic of School of Bio-Science and Food Engineering Changchun University of Science and Technology Changchun130600 China Center for Food and Bio Innovation Dong-A University Busan49315 Korea Republic of Nutritional Education Major Graduate School of Education Dong-A University Busan49315 Korea Republic of Nutrinomics Lab. Co. Ltd. Busan49315 Korea Republic of

The study determined the effect of incorporating Momordica charantia leaf powder (MCLP) into corn-starch 3D food-printing ink as a functional ingredient. The effects of the particle size (75, 131, and 200 μm) and quantity of MCLP on 3D printing performance, structural, textural, and rheological properties of corn starch gel were evaluated with different concentrations (5, 10, and 15% (w/w)) of corn starch. The viscoelastic properties of food inks were determined considering their behavior during extrusion and self-recovery after printing. Scanning electron microscope was used to characterize the microstructure. Based on the results, a high starch content (15%) with 5% MCLP was more favorable for 3D food printing. In addition, 3D printing performance, textural and rheological properties of formulated ink was mainly governed by the particle size of MCLP. The food ink with a 5% mass fraction of 200 μm MCLP had the highest printing precision and the best masticatory properties. © 2023, The Authors. All rights reserved.

关键词： Particle size

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Development and Validation of a Current-BasedEEG System

Development and Validation of a Current-BasedEEG System

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IEEE biomedical Circuits and Systems (BIOCAS)

作者： Daniel Comaduran Marquez Sarah J. Anderson Kent Hecker Kartikeya Murari Biomedical Engineering Graduate Program University of Calgary Calgary Canada Faculty of Veterinary Medicine University of Calgary Calgary Canada Electrical and Computer Engineering University of Calgary Calgary Canada

Electroencephalography (EEG) measures electrical brain activity in a noninvasive manner. EEG mainly records electrical activity from radially oriented pyramidal cells in the cerebral cortex. However, EEG is less influenced by the tangentially oriented pyramidal cells. Magnetoencephalography (MEG) is influenced by the tangentially oriented pyramidal cells. However, MEG is not as widely available as EEG. Recent studies show that the combined used of EEG and MEG can improve the accuracy of source reconstruction, especially in neurological disorders (e.g. epilepsy). A current-based EEG system could allow us to record from the tangentially oriented pyramidal cells. The current work presents the development and validation of such a current-based EEG system. The system is adapted from a previously developed current-based electromyography (EMG) system. Characterization data and pilot EEG recordings in a human subject are presented. Further work will focus on miniaturizing the system to interface with the standard EEG cap, as well as developing a multichannel system.

关键词： Electroencephalography Electrodes Current measurement Power supplies Instruments Frequency response Electromyography

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Stabilizing deep tomographic reconstruction

arXiv

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arXiv 2020年

作者： Wu, Weiwen Hu, Dianlin Cong, Wenxiang Shan, Hongming Wang, Shaoyu Niu, Chuang Yan, Pingkun Yu, Hengyong Vardhanabhuti, Varut Wang, Ge Biomedical Imaging Center Center for Biotechnology and Interdisciplinary Studies Department of Biomedical Engineering Rensselaer Polytechnic Institute TroyNY United States The Laboratory of Image Science and Technology Southeast University Nanjing China Institute of Science and Technology for Brain-inspired Intelligence Fudan University Shanghai China Department of Electrical & Computer Engineering University of Massachusetts Lowell LowellMA United States Department of Diagnostic Radiology Li Ka Shing Faculty of Medicine The University of Hong Kong Hong Kong SAR Hong Kong

Tomographic image reconstruction with deep learning is an emerging field, but a recent landmark study reveals that several deep reconstruction networks are unstable for computed tomography (CT) and magnetic resonance imaging (MRI). Specifically, three kinds of instabilities were reported: (1) strong image artefacts from tiny perturbations, (2) small features missing in a deeply reconstructed image, and (3) decreased imaging performance with increased input data. On the other hand, compressed sensing (CS) inspired reconstruction methods do not suffer from these instabilities because of their built-in kernel awareness. For deep reconstruction to realize its full potential and become a mainstream approach for tomographic imaging, it is thus critically important to meet this challenge by stabilizing deep reconstruction networks. Here we propose an Analytic Compressed Iterative Deep (ACID) framework to address this challenge. ACID synergizes a deep reconstruction network trained on big data, kernel awareness from CS-inspired processing, and iterative refinement to minimize the data residual relative to real measurement. Our study demonstrates that the deep reconstruction using ACID is accurate and stable, and sheds light on the converging mechanism of the ACID iteration under a Bounded Relative Error Norm (BREN) condition. In particular, the study shows that ACID-based reconstruction is resilient against adversarial attacks, superior to classic sparsity-regularized reconstruction alone, and eliminates the three kinds of instabilities. We anticipate that this integrative data-driven approach will help promote development and translation of deep tomographic image reconstruction networks into clinical applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Compressed sensing

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Deep learning-based frozen section to FFPE translation

arXiv

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arXiv 2021年

作者： Ozyoruk, Kutsev Bengisu Can, Sermet Gokceler, Guliz Irem Başak, Kayhan Demir, Derya Serin, Gurdeniz Hacisalihoglu, Uguray Payam Kurtuluş, Emirhan Darbaz, Berkan Lu, Ming Y. Chen, Tiffany Y. Williamson, Drew F.K. Yilmaz, Funda Mahmood, Faisal Turan, Mehmet Institute of Biomedical Engineering Bogazici University Istanbul Turkey Uk Biocentre Tilbrook United Kingdom Department of Pathology Brigham and Women's Hospital Harvard Medical School BostonMA United States Cancer Data Science Program Dana-Farber Cancer Institute BostonMA United States Cancer Program Broad Institute of Harvard and Mit CambradgeMA United States Saǧlik Bilimleri University Kartal Dr.Lütfi Kirdar City Hospital Department of Pathology Istanbul Turkey Faculty of Medicine Department of Pathology Ege University Izmir Turkey Istanbul Yeni Yuzyil University Medical Faculty Gaziosmanpasa Hospital Pathology Department Turkey

Frozen sectioning (FS) is the preparation method of choice for microscopic evaluation of tissues during surgical operations. The high speed of procedure allows pathologists to rapidly assess the key microscopic features, such as tumor margins and malignant status to guide surgical decision-making and minimise disruptions to the course of the operation. However, FS is prone to introducing many misleading artificial structures (histological artefacts), such as nuclear ice crystals, compression, and cutting artefacts, hindering timely and accurate diagnostic judgement of the pathologist. Additional training and prolonged experience is often required to make highly effective and time critical diagnosis on frozen sections. On the other hand, the gold standard tissue preparation technique of formalin-fixation and paraffin-embedding (FFPE) provides significantly superior image quality, but is a very time-consuming process (12-48 hours), making it unsuitable for intra-operative use. In this paper, we propose an artificial intelligence (AI) method that improves FS image quality by computationally transforming frozen-sectioned whole-slide images (FS-WSIs) into whole-slide FFPE-style images in minutes. AI-FFPE rectifies FS artefacts with the guidance of an attention-mechanism that puts a particular emphasis on artefacts while utilising a self-regularization mechanism established between FS input image and synthesized FFPE-style image that preserves clinically relevant features. As a result, AI-FFPE method successfully generates FFPE-style images without significantly extending tissue processing time and consequently improves diagnostic accuracy. We demonstrate the efficacy of AI-FFPE on lung and brain frozen sections using a variety of different qualitative and quantitative metrics including visual Turing tests from 20 board certified pathologists. Additionally, we demonstrate that deep models trained on FFPE tissue can adapt to frozen sections which a much higher efficacy whe

关键词： Surgery

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A hypoxia-activated copper ion nanoexchanger for cancer immunotherapy by in situ precise production of immunogenic cell death inducer

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Chinese Chemical Letters 2025年

作者： Xinlu Zhang Yongxin Liu Huan Li Shutong Chen Guocheng Wang Xu Zhang Chen Cao Xiaoyuan Chen Sheng Wang School of Life Sciences Faculty of Medicine Tianjin University Tianjin 300072 China Department of Diagnostic Radiology Yong Loo Lin School of Medicine National University of Singapore Singapore 119074 Singapore Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore Singapore 117575 Singapore Department of Biomedical Engineering College of Design and Engineering National University of Singapore Singapore 117575 Singapore Department of Pharmacy and Pharmaceutical Sciences Faculty of Science National University of Singapore Singapore 117544 Singapore Clinical Imaging Research Centre Centre for Translational Medicine Yong Loo Lin School of Medicine National University of Singapore Singapore 117599 Singapore Nanomedicine Translational Research Program Yong Loo Lin School of Medicine National University of Singapore Singapore 117597 Singapore Theranostics Center of Excellence (TCE) Yong Loo Lin School of Medicine National University of Singapore Singapore 138667 Singapore Institute of Molecular and Cell Biology Agency for Science Technology and Research (A*STAR) Singapore 138673 Singapore

In situ therapeutic agent production strategy is promising to overcome the drawbacks of direct drug delivery. Hypoxia provides a great target for precise treatment of tumor. Here we report a copper ion competition-based nanoparticle (NP) for hypoxia-activated formation of diethyldithiocarbamate (DTC)-copper complex, an immunogenic cell death (ICD) inducer. The NP is composed of an amphiphilic hypoxia-responsive DTC precursor and a fluorescence quenched copper ion-chelated squaric acid. In hypoxic tumor cells, the azobenzene linker in DTC precursor can be cleaved through bioreduction, leading to DTC release and subsequent copper ion exchange between DTC and squaric acid. Simultaneous formation of toxic DTC-copper complexes and fluorescence recovery will allow for visualization of in situ therapeutic agents production. Furthermore, the DTC-copper complexes can induce ICD and promote cytotoxic T lymphocyte infiltration for cancer immunotherapy. This study not only provides a promising hypoxia-activated nanomedicine for precision cancer therapy, but also a visualization strategy for evaluating the treatment process.

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Simulation and computational analysis of fire sprinkle bulb activation with variation of liquid and wall thickness

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AIP Conference Proceedings 2020年第1期2314卷

作者： Alfian Pramudita Putra Erik Jan Westerman Akif Rahmatillah 1Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 2Department of Biomedical Engineering Faculty of Science and Engineering University of Groningen Groningen The Netherlands

Fire sprinkler is a safety system that is active when fire is detected. It consists of a bulb that holds the water flow and made of glass with liquid inside. The increase of temperature in its environment would expand the volume of the liquid and break the glass which leads to water spray to extinguish the fire. This study aims to model and simulate the fire sprinkler bulb and optimize several parameters related to its activation including the thickness of the bulb, type of liquid and the ratio of air and liquid inside the bulb. The modeling and simulation was performed in COMSOL Multiphysics with variation of wall thickness and liquid inside the bulb. The result showed that the best parameter was the liquid of glycerol, a height of 17.5 mm and a glass thickness of 0.1 mm, this resulted in the air to liquid ratio of 0.0042428 and breaking time of 7.2400s. This result was the fastest breaking time towards several simulations. For future study, several parameters need to be considered in the simulation to minimize the gap between the simulation and the actual condition, such as room condition, and water pressure.

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