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Antimicrobial Photodynamic Effectiveness of Light Emitting Diode (Led) for Inactivation on Staphylococcus aureus Bacteria and Wound Healing in Infectious Wound Mice 3

Antimicrobial Photodynamic Effectiveness of Light Emitting D...

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3rd Annual Scientific Meeting on Medical physics and Biophysics, PIT-FMB in conjunction with the 17th South-East Asia Congress of Medical physics, SEACOMP 2019

作者： Astuti, S.D. Ardyana, Y. Arifianto, D. Winarno Puspita, P.S. Yuwana, Y.G.Y. Pradhana, A.A.S. Department of Physics Faculty of Sciences and Technology Airlangga University Surabaya Indonesia Biomedical Engineering Program Department of Physics Faculty of Sciences and Technology Airlangga University Surabaya Indonesia Faculty of Vocational Airlangga University Surabaya Indonesia

This study aims to determine the effectiveness of the antimicrobial photodynamic therapy (aPDT) LEDs of 392 nm and 628 nm red LEDs for photoinactivation on Staphylococcus aureus in vitro and the photodynamic effectiveness of therapy for wound healing in mice in vivo. The sample used was Staphylococcus aureus bacterial isolate which was infected on mice incision wounds. The LED exposure was carried out at the energy density of 19.44 J/cm2, respectively. In vitro test samples were divided into three groups, namely (P0): control group, (P1): LED treatment group 392 nm, (P2): LED treatment group 628 and (P3): LED combination treatment group 392 and 628 nm. In the in vivo test, the mice of infectious wound models were divided into 5 namely (M+): positive control group, (M-): negative control group, (M1): LED treatment group 392 nm, (M2): LED treatment group 628 and (M3): LED combination treatment group 392 and 628 nm. The results of in vitro studies showed an increase in the photoinactivation effect on LED exposure, with the effectiveness of inactivation on the LED 392 nm at 67.10%. The effect of photoinactivation of bacteria on wounds in vivo due to photodynamic therapy in the red LED exposure group was 88%, blue LED exposure group was 94%, exposure combination group of red and blue LEDs was 95%. So, the antimicrobial photodynamic therapy LEDs are effective for bacterial inactivation and accelerate wound healing in mice. © Published under licence by IOP Publishing Ltd.

关键词： Light emitting diodes

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Biodegradable Pbat/Pla Blend Films Incorporated with Turmeric and Cinnamomum Powder: A Potential Alternative for Active Food Packaging

SSRN

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SSRN 2023年

作者： de Castro, Layara L.R.L. Abreu, Iago R. Braz, Cristiano J.F. Rodrigues, Samara C.S. dos Araújo, Regilda S.R.M. Folkersma, Rudy de Carvalho, Laura H. Barbosa, Renata Alves, Tatianny S. Graduate Program in Materials Science and Engineering Federal University of Piauí Teresina64.049-550 Brazil Department of Physics Federal Institute of Education Science and Technology of Piauí Teresina Central Campus Teresina64.000-040 Brazil Department of Nutrition Federal University of Piauí Teresina64.049-550 Brazil NHL Stenden University of Applied Sciences Groningen9727 Netherlands Graduate Program in Materials Science and Engineering Federal University of Campina Grande PI TeresinaCEP: 58.100-000 Brazil

Active packaging made from biodegradable polymers and natural additives appears as an ecological alternative. In addition to having antioxidant activity and enhancing food preservation, it allows mitigating the negative impacts caused by improper disposal. This study pursued to produce biodegradable films based on a polymer blend PBAT/PLA (Ecovio®) using the flat extrusion method. The films were prepared with the incorporation of 5 wt% of powdered turmeric or cinnamon as natural additives. The films obtained, and those reprocessed twice, were characterized in terms of colorimetric, UV light transmittance, water contact angle, water vapor permeability, morphology, mechanical properties, and antioxidant activity. Cinnamon reduced the UV light transmittance and made a surface more hydrophobic. Reprocessing led to greater elongation and maximum load, associated with increased dispersion and distribution, as evidenced in the morphological analysis. The films developed have significant potential for applications in active food packaging, with emphasis on cinnamon-additivated films. © 2023, The Authors. All rights reserved.

关键词： Biodegradable polymers

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Effect of PDI on the bacterial behavior of clinically important Gram negatives

Effect of PDI on the bacterial behavior of clinically import...

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Latin America Optics and Photonics Conference, LAOP 2022

作者： Vieira, R.L. Machado, J.S. Corrêa, T.Q. Blanco, K.C. Bagnato, V.S. Biotechnology Graduate Program Federal University of São Carlos SP - Rod. Washington Luiz Monjolinho SP São Carlos13565-905 Brazil São Carlos Institute of Physics University of São Paulo PO Box 369 SP São Carlos13560-970 Brazil Department of Biomedical Engineering Texas A&M University College StationTX77843 United States

Photodynamic inactivation with a subdose of light and curcumin as a photosensitizer causes effects on the bacterial behavior of important pathogenic Gram negatives, which may receive antibiotic resistance genes, becom... 详细信息

ISBN: (纸本)9781957171135

关键词： Photosensitizers

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Empowering Precision Medicine: AI-Driven Schizophrenia Diagnosis via EEG Signals: A Comprehensive Review from 2002-2023

arXiv

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arXiv 2023年

作者： Jafari, Mahboobeh Sadeghi, Delaram Shoeibi, Afshin Alinejad-Rokny, Hamid Beheshti, Amin García, David López Chen, Zhaolin Acharya, U. Rajendra Gorriz, Juan M. Internship in BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia Data Science and Computational Intelligence Institute University of Granada Spain BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia UNSW Data Science Hub The University of New South Wales SydneyNSW2052 Australia Health Data Analytics Program Centre for Applied Artificial Intelligence Macquarie University Sydney2109 Australia Data Science Lab School of Computing Macquarie University SydneyNSW2109 Australia Monash University Melbourne Australia School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia Department of Psychiatry University of Cambridge United Kingdom

Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional, and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of motivation, and difficulties in concentration. While the exact causes of SZ remain unproven, factors such as brain injuries, stress, and psychotropic drugs have been implicated in its development. SZ can be classified into different types, including paranoid, disorganized, catatonic, undifferentiated, and residual. Diagnosing SZ involves employing various tools, including clinical interviews, physical examinations, psychological evaluations, the Diagnostic and Statistical Manual of Mental Disorders (DSM), and neuroimaging techniques. Electroencephalography (EEG) recording is a significant functional neuroimaging modality that provides valuable insights into brain function during SZ. However, EEG signal analysis poses challenges for neurologists and scientists due to the presence of artifacts, long-term recordings, and the utilization of multiple channels. To address these challenges, researchers have introduced artificial intelligence (AI) techniques, encompassing conventional machine learning (ML) and deep learning (DL) methods, to aid in SZ diagnosis. This study reviews papers focused on SZ diagnosis utilizing EEG signals and AI methods. The introduction section provides a comprehensive explanation of SZ diagnosis methods and intervention techniques. Subsequently, review papers in this field are discussed, followed by an introduction to the AI methods employed for SZ diagnosis and a summary of relevant papers presented in tabular form. Additionally, this study reports on the most significant challenges encountered in SZ diagnosis, as identified through a review of papers in this field. Future directions to overcome these challenges are also addressed. The discussion section examines the specific details of each paper, culminating in the presentation of conclusions and findings. © 2023,

关键词： Electroencephalography

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Biophysics of amplitude-modulated giga-hertz electromagnetic waves stimulation

Biophysics of amplitude-modulated giga-hertz electromagnetic...

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Asilomar Conference on Signals, Systems & Computers

作者： Fatima Ahsan Aravind C. Govindaraju Robert M. Raphael Taiyun Chi Sameer A. Sheth Wayne Goodman Behnaam Aazhang Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curly Institute Rice University Houston TX Department of Bioengineering Rice University Houston TX USA Department of Neurosurgery Baylor College of Medicine Houston TX USA Menninger Department of Psychiatry and Behavioral Sciences Baylor College of Medicine Houston TX USA

This paper presents the biophysical modeling for neuronal stimulation caused by amplitude-modulated giga-hertz (GHz) electromagnetic (EM) waves. We model a 1D cable equation for electrical signal propagation in a vestibular ganglion neuronal fiber and use Hodgkin-Huxley formalism to model voltage-dependent channel conductances. We find out that for a given stimulation signal strength, the GHz waveform amplitude-modulated at a low frequency of Δf causes neuronal firing with the frequency of Δf whereas the continuous wave GHz did not elicit any neuronal firing. Moreover, the voltage-dependent channel gating dynamics of the Δf amplitude-modulated GHz stimulation matches that of a simple low frequency stimulation at Δf. Additionally, we find that the modulation depth controls the firing rate of the neurons. The significance of this property is that the amplitude modulation caused by the interference of two similar high frequency signals could be leveraged to focally excite neurons at depth without stimulating overlying cortical regions. These theoretical predictions based on the Hodgkin-Huxley model can later be tested experimentally.

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Exploring Nitration Effects on Electroporation: Enhancing Cold Plasma Biomedicine

Exploring Nitration Effects on Electroporation: Enhancing Co...

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IEEE International Conference on Plasma Science (ICOPS)

作者： D. Abduvokhidov M. Niyozaliev Z. Chen J. Razzokov Institute of Fundamental and Applied Research National Research University TIIAME Tashkent Uzbekistan Institute of Material Sciences Academy of Sciences of Uzbekistan Tashkent Uzbekistan Department of Physics National University of Uzbekistan Tashkent Uzbekistan Department of Information Technologies Tashkent International University of Education Tashkent Uzbekistan Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Center for Advanced Therapy National Innovation Center for Advanced Medical Devices Shenzhen China New Uzbekistan University R&D Center Tashkent Uzbekistan Department of Biomedical Engineering Tashkent State Technical University Tashkent Uzbekistan

ISBN: (数字)9798350360912

ISBN: (纸本)9798350360929

Electroporation, the transient alteration of cell membrane permeability induced by electric fields, constitutes a fundamental technique in biomedicine, facilitating gene transference, pharmaceutical transport, and oncological therapy. Despite its widespread utility, the impact of nitration, a biochemical alteration entailing the introduction of nitro groups into phospholipids, on electroporation dynamics remains insufficiently investigated. In this study, we employ molecular dynamics simulations to examine the influence of nitration on pore formation during electroporation. Through systematic manipulation of nitration levels and electric field intensities, we explore the nuanced interaction between nitration and electroporation kinetics. Our simulations disclose that augmenting nitration levels markedly expedites pore generation, evidenced by notable reductions in pore formation durations observed at elevated nitration percentages and intensified electric fields. This phenomenon underscores the modulatory function of nitration in reshaping the kinetics of electroporation. Furthermore, considering the relevance to cold plasma applications, we emphasize the potential implications of these findings in the context of cold plasma-mediated cancer therapy and biomedical treatments. Moreover, our investigation elucidates the intricate mechanisms governing this phenomenon, furnishing crucial insights for refining electroporation protocols in gene therapy, drug conveyance, plasma-based cancer therapy, and associated biomedical applications. These findings shed light on the synergistic interplay between nitration, electroporation, and cold plasma, charting a course for future advancements in this pivotal domain of plasma science.

关键词： Plasma applications Systematics Protocols Refining Electroporation Kinetic theory Permeability

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Alternating Deep Low-Rank Approach for Exponential Function Reconstruction and Its biomedical Magnetic Resonance Applications

arXiv

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arXiv 2022年

作者： Huang, Yihui Wang, Zi Zhang, Xinlin Cao, Jian Tu, Zhangren Lin, Meijin Guo, Di Qu, Xiaobo The Department of Electronic Science Biomedical Intelligent Cloud Research and Development Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Xiamen University Xiamen China The College of Physics and Information Engineering Fuzhou University Fuzhou China The Department of Applied Marine Physics and Engineering College of Ocean and Earth Sciences Xiamen University China The School of Computer and Information Engineering Xiamen University of Technology Xiamen China

Undersampling can accelerate the signal acquisition but at the cost of bringing in artifacts. Removing these artifacts is a fundamental problem in signal processing and this task is also called signal reconstruction. Through modeling signals as the superimposed exponential functions, deep learning has achieved fast and high-fidelity signal reconstruction by training a mapping from the undersampled exponentials to the fully sampled ones. However, the mismatch, such as the sampling rate of undersampling, the organ and the contrast of imaging, between the training and target data will heavily compromise the reconstruction. To address this issue, we propose Alternating Deep Low-Rank (ADLR), which combines deep learning solvers and classic optimization solvers. Experiments on the reconstruction of synthetic and realistic biomedical magnetic resonance signals demonstrate that ADLR can effectively mitigate the mismatch issue and achieve lower reconstruction errors than state-of-the-art methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Exponential functions

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Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet in Fields up to 25 T

Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet i...

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JSAP-OSA Joint Symposia, JSAP 2021

作者： Bao, J. Peraca, N. Marquez Tay, F. Kritzell, T.E. Li, X. Noe, G.T. Katayama, I. Takeda, J. Nojiri, H. Yamahara, H. Tabata, H. Baydin, A. Kono, J. Department of Physics and Astronomy Rice University HoustonTX United States Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX United States Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama Japan Institute for Materials Research Tohoku University Sendai Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering University of Tokyo Japan Smalley-Curl Institute Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States

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Fabrication and bioactivity studies of wollastonite/polycaprolactone composites

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International Journal of Nano and Biomaterials 2023年第2期10卷 86-99页

作者： Lakshmi, R. Choudhary, Rajan Senatov, Fedor Kaloshkin, Sergey Kothandam, Shobana Ponnamma, Deepalekshmi Sadasivuni, Kishor Kumar Swamiappan, Sasikumar Department of Chemistry Auxilium College Tamil Nadu Vellore632006 India Faculty of Materials Science and Applied Chemistry Rudolfs Cimdins Riga Biomaterials Innovations and Development Centre of RTU Institute of General Chemical Engineering Riga Technical University Pulka St 3 RigaLV-1007 Latvia Baltic Biomaterials Centre of Excellence Headquarters at Riga Technical University Kipsala Street 6A RigaLV-1048 Latvia National University of Science and Technology "MISiS" Moscow119049 Russia Department of Chemistry School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore632014 India Materials Science and Technology Program Department of Mathematics Statistics and Physics College of Arts and Sciences Qatar University P.O. Box 2713 Doha Qatar Center for Advanced Materials Qatar University P.O. Box 2713 Doha Qatar Department of Chemistry School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore632014 India

Current work investigates the influence of wollastonite on mechanical stability and biomineralisation ability of wollastonite/ polycaprolactone (PCL) composites (WP composites). The solvent casting particulate leaching method was used to prepare these composites. FT-IR spectra indicated the presence of functional groups associated with PCL and wollastonite. Scanning electron microscopy showed aggregated morphology and wollastonite particles were embedded in the PCL matrix. The incorporation of wollastonite leads to a more than three-fold increase in the compressive strength of the composites. Moreover, the composites containing 50% wollastonite exhibited better compressive strength than 80%. This observation suggested that if the concentration of a filler is exceeded beyond its critical concentration then the mechanical stability of the composite will be compromised. The composites revealed good apatite deposition ability. Thus, the biomineralisation ability and compressive strength of PCL can be improved by preparing its composites with bioceramics. © 2023 Inderscience Enterprises Ltd.

关键词： Bioceramics

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DCGAN-based Medical Image Augmentation to Improve ELM Classification Performance

DCGAN-based Medical Image Augmentation to Improve ELM Classi...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Rando Noor Akhmad Setiawan Adhistya Erna Permanasari Riries Rulaningtyas Andriyan Bayu Suksmono Imas Sukaesih Sitanggang Dept. of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia Dept. of Physics Universitas Airlangga Biomedical Engineering Program Surabaya Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Department of Computer Science IPB University Bogor Indonesia

ISBN: (数字)9781665460309

ISBN: (纸本)9781665460316

Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%.

关键词： Satellites Extreme learning machines Medical services Feature extraction Generative adversarial networks Entropy Lesions

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