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A physical picture of liquid–liquid phase separation of proteins

Journal of Molecular Liquids 2025年 424卷

作者： Kinoshita, Masahiro Hayashi, Tomohiko Nakamura, Yuka Yoshimori, Akira Katahira, Masato Nagata, Takashi Department of Chemistry of Science Chiba University 1-33 Yayoi-cho Inage Chiba263-8522 Japan Institute of Advanced Energy Kyoto University Kyoto Uji611-0011 Japan Interdisciplinary Program of Biomedical Engineering Assistive Technology and Art and Sports Sciences Faculty of Engineering Niigata University 8050 Ikarashi 2-no-cho Nishi-ku Niigata950-2181 Japan Department of Physics Niigata University Niigata950-2181 Japan

Liquid-liquid phase separation (LLPS) of proteins, by which they assemble and partition into a protein-dense phase and a protein-dilute phase, has caught much attention due to its essential roles in a variety of biological processes. Nevertheless, its mechanism remains to be unveiled. Here we develop a physical picture covering almost all the aspects of LLPSs of diverse systems. In our view, when only the proteins are looked at, one of the two phases is liquid-like and the other is gas-like. We relate LLPS to gas–liquid phase separation (GLPS) of simple fluids wherein the pivotal quantity is kBT (kB is the Boltzmann constant and T is the absolute temperature) divided by the absolute value of the minimum of interaction potential between fluid particles. GLPS occurs only if the pivotal quantity is sufficiently small. For LLPS, the interaction potential must be replaced by the potential of mean force (PMF) between protein molecules in aqueous solution. We do not explicitly consider aqueous solution, and its influence on properties of protein molecules is incorporated in PMF. PMF can reach its deep minimum when the two protein molecules associate. A physical interpretation is given for GLPS from a statistical-mechanics point of view, and it is extended to LLPS. In the extension, we discuss not only the similarities between the two phase separations but also the physical factors to be taken into account only in LLPS due to the fact that proteins are large molecules possessing polyatomic structures and they are immersed in aqueous solution. LLPS can be categorized as a biological self-assembly process. By reconsidering the results obtained in our earlier studies on biological self-assembly processes, we specify the entropic and energetic factors driving or opposing coacervation (association) of protein molecules followed by LLPS. We clarify the differences between LLPSs of folded proteins (i.e., proteins in the native states) and intrinsically disordered proteins. There c

关键词： Alkali halides

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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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International Electrical engineering Congress (iEECON)

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

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.

关键词： Training Support vector machines Machine learning algorithms Hospitals Stroke (medical condition) Predictive models Prediction algorithms

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Application of Acinetobacter indicus to promote cigarette smoke particulate matter phytoremediation: removal efficiency and plant–microbe interactions

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Environmental Science and Pollution Research 2024年第39期31卷 52352-52370页

作者： Nookongbut, Phitthaya Thiravetyan, Paitip Salsabila, Salma Widiana, Ana Krobthong, Sucheewin Yingchutrakul, Yodying Treesubsuntorn, Chairat School of Bioresources and Technology King Mongkut’s University of Technology Thonburi Bangkok10150 Thailand Department of Biology Faculty of Science and Technology State Islamic University Sunan Gunung Djati Bandung West Java Bandung City40614 Indonesia Interdisciplinary Graduate Program in Genetic Engineering Kasetsart University Bangkok10900 Thailand Proteomics Research Team National Omics Center NSTDA Khlong Luang Pathum Thani12120 Thailand Pilot Plant Development and Training Institute King Mongkut’s University of Technology Thonburi Bangkok10150 Thailand

Particulate matter (PM) is one of the most hazardous atmospheric pollutants. Several plant species show high potential to reduce air pollutants and are widely used as green belts to provide clean outdoor spaces for human well-being. However, high PM concentrations cause physiological changes and stress in plants. In this study, 11 species of Thai native perennial plants were exposed to PM generated from tobacco smoke. Wrightia religiosa (Teijsm. & Binn.) Benth. ex Kurz, Bauhinia purpurea DC. ex Walp. and Tectona grandis L.f. reduced PM effectively (which is in the typical range of 43.95 to 52.97%) compared to other plant species. In addition, the responses of perennial plants under PM stress at the proteomic level were also evaluated. Proteomic analysis of these three plant species showed that plants respond negatively to high PM concentrations, such as reducing several photosynthetic-related proteins and increasing plant stress response proteins. To improve PM phytoremediation efficiency and reduce plant stress from PM, perennial plant–microbe interactions were investigated. W. religiosa was inoculated with Acinetobacter indicus PS1, and high biosurfactant-producing strains clearly showed a higher PM removal efficiency than non-inoculated plants (9.48, 9.5 and 12.6% for PM1.0, PM2.5 and PM10, respectively). Inoculating W. religiosa with A. indicus PS1 maintained chlorophyll a and b concentrations. Moreover, the malondialdehyde (MDA) concentration of W. religiosa inoculated with A. indicus PS1 was lower than that of non-inoculated W. religiosa. The leaf wax content (µg/cm2) and biosurfactant (µg/cm2) of W. religiosa inoculated with A. indicus PS1 were also higher than those of non-inoculated W. religiosa. This study clearly showed that inoculating plants with A. indicus PS1 can help plants remediate PM and improve their PM stress response. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Air pollution

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3DECG-Net: ECG fusion network for multi-label cardiac arrhythmia detection

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Computers in Biology and Medicine 2024年 182卷 109126-109126页

作者： Sadeghi, Alireza Hajati, Farshid Rezaee, Alireza Sadeghi, Mahdieh Argha, Ahmadreza Alinejad-Rokny, Hamid Department of Mechatronics School of Intelligent Systems College of Interdisciplinary Science and Technology University of Tehran Tehran Iran School of Science and Technology Faculty of Science Agriculture Business and Law University of New England ArmidaleNSW2350 Australia Student Research Committee Mazandaran University of Medical Sciences Sari Iran School of Biomedical Engineering UNSW Sydney RandwickNSW2052 Australia BioMedical Machine Learning Lab School of Biomedical Engineering UNSW Sydney RandwickNSW2052 Australia

Cardiovascular diseases represent the leading global cause of death, typically diagnosed and addressed through electrocardiograms (ECG), which record the heart's electrical activity. In recent years, there has been a notable surge in ECG recordings, driven by the widespread use of wearable devices. However, the limited availability of medical experts to analyze these recordings underscores the necessity for automated ECG analysis using computer-aided methods. In this study, we introduced 3DECG-Net, a deep learning model designed to detect and classify seven distinct heart states through the analysis of data fusion from 12-lead ECG in a multi-label framework. Our model leverages a residual architecture with a multi-head attention mechanism, undergoing training within a five-fold cross-validation scheme. By transforming 12-lead ECG signals into 3D data with the help of Recurrent Plot technique, 3DECG-Net achieves a noteworthy micro F1-score of 80.3 %, surpassing the performance of other state-of-the-art deep learning models developed for this specific task. Also, we present an ECG preprocessing framework to generate compact, high-quality ECG signals for potential application in future studies within this domain. We conduct an explainable AI experiment using Local Interpretable Model-agnostic Explanations (LIME) to elucidate the significance of each lead in accurately diagnosing specific arrhythmias, ensuring the logical processing of ECG data by 3DECG-Net. The findings of this study suggest that the proposed model is trustworthy and has the potential to be used as an effective diagnostic toolset for identifying heart arrhythmias. Its effectiveness can improve the diagnostic process, facilitate early treatment, and enhance overall efficiency in medical settings. © 2024

关键词： Data fusion

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Initial Results on Primary Field Cancellation of Magnetic Induction Spectroscopy Technique for Fetal Acidosis Detection using COMSOL Multiphysics

Initial Results on Primary Field Cancellation of Magnetic In...

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2021 International Conference on biomedical engineering, ICoBE 2021

作者： Halim, S.F. Abdul Zakaria, M.H. Zakaria, Z. Norali, A.N. Noor, A. Mohd Ahmed, A.A. Pusppanathan, J. Rahiman, M.H. Fazalul Muji, S.Z. Mohd Rahim, R. Abdul Biomedical Electronic Engineering Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Arau Perlis 02600 Malaysia Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Mechatronic Engineering Program Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Malaysia Electronic Engineering Department Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia School of Electrical Engineering Faculty of Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia

Monitoring of fetal condition during labor could save hundred lives in a single year. During labor, fetus is at critical condition as acidosis may occur suddenly without any early symptoms. Invasive method such as Fetal Blood Sampling (FBS) has been used to detect the decline in pH level of fetus. However, fetal loss rate after FBS may range from 1.4% up to 25%. In this paper, magnetic field induction spectroscopy was implemented to determine fetal acidosis by using primary magnetic field cancellation technique. Magnetic Induction Spectroscopy (MIS) probe was design where transmitter coil (TX) is perpendicular to receiver coil (RX). The result shows that the secondary magnetic field produced have been successfully measured without any interruption from primary magnetic field. By using transmitter input 1A, it shows that voltage is inversely proportional to the blood pH due to the conductivity properties of blood. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Spectroscopy

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Printability and cytotoxicity of alginate/agarose hydrogel with carboxylmethyl cellulose and apple powder

Printability and cytotoxicity of alginate/agarose hydrogel w...

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biomedical engineering International Conference (BMEiCON)

作者： K. Chessadangkul N. Damrongplasit S. Morakul T. Tharasanit A. Pimpin Biomedical engineering program Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Obstetrics Gynaecology and Reproduction Faculty of Veterinary Science Chulalongkorn University Bangkok Thailand Department of Mechanical engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781665489041

The cultured meat is the solution to reduce resources using in a traditional meat production. It helps produce meat without killing livestock and decrease residue products. The method could also integrate with scaffold’s material which does not derive from animal products. This study aims to investigate the effects of carboxymethyl cellulose (CMC) and apple powder on printability and cytotoxicity as additives in alginate/agarose-based hydrogel. 3D structures of them were printed to find a proper printing condition. From our experiments, the structure could maintain their shapes and uniform line sizes for carboxylmethyl cellulose, but not for apple powder at the 2% w/v alginate and 0.8% w/v agarose. However, the combination of them could be printed well. In parallel, 293FT cells were cultured with hydrogel drop to test cytotoxicity. It showed that the hydrogel with both additives does not harm cells during 8-day culturing.

关键词： Viscosity Printing Powders Additives Toxicology Three-dimensional displays Shape

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The Fluorescent Effect of Chitosan Magnetitic Nanoparticles for Near-Infrared Imaging 3

The Fluorescent Effect of Chitosan Magnetitic Nanoparticles ...

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3rd Novel Intelligent and Leading Emerging Sciences Conference, NILES 2021

作者： Abuelmakarem, Hala S. Ahmed, Wafaa A. Mofed, Dina Wael, Mohammed Sami, Sherif A. The Higher Institute of Engineering Elshrouk Academy Biomedical and Systems Engineering Department Egypt Biochemistry and Molecular Biology Unit National Cancer Institute Cairo University Cancer Biology Department Giza Egypt Cairo University Zoology graduate program Department of zoology Faculty of science Giza Egypt Cairo University Faculty of Engineering Department of Biomedical Engineering and Systems Giza Egypt

ISBN: (纸本)9781665421577

Early cancer detection increases the healing rate according to the cancer stage. Nanotechnology is an advanced technique in cancer management due to the permeability and retention effect. Nano contrast agents are chief in early cancer detection because they diffuse in the cancerous tissue due to permeability and retention. This study aims to synthesize Chitosan Magnetic Nanoparticles (CM NPS) to evaluate them as a contrast agent for cells imaging, in vitro, under near-infrared irradiation. CM NPs were synthesized using the wetted chemical method. They were characterized using Dynamic Light Scattering, High-resolution Transmission Electronic Microscopy (HR- TEM), Fourier Transform Infrared (FTIR) Spectroscopy, and X-ray diffraction (XRD). The shining effect of the CM NPs was evaluated under the inverted microscopy over through a human lung epithelial cell culture in vitro. The characterization results ensured the successful synthesis of CM NPs. The photomicrographs appeared shining light of CM NPs on the cells photographed under the inverted microscope. © 2021 IEEE.

关键词： Chitosan

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A comprehensive overview of diffuse correlation spectroscopy: theoretical framework, recent advances in hardware, analysis, and applications

arXiv

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arXiv 2024年

作者： Wang, Quan Pan, Mingliang Kreiss, Lucas Samaei, Saeed Carp, Stefan A. Johansson, Johannes D. Zhang, Yuanzhe Wu, Melissa Horstmeyer, Roarke Diop, Mamadou Li, David Day-Uei University of Strathclyde Department of Biomedical Engineering Faculty of Engineering Glasgow United Kingdom Duke University Department of Biomedical Engineering DurhamNC United States Western University Department of Medical and Biophysics Schulich School of Medical & Dentistry LondonON Canada Harvard Medical School Massachusetts General Hospital Optics at Athinoula A. Martinos Center for Biomedical Imaging CharlestownMA United States Linköping University Department of Biomedical Engineering Linköping Sweden Imaging Program Lawson Health Research Institute LondonON Canada

Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry into this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, fibers, and correlators), as well as new data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed, and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research. Copyright © 2024, The Authors. All rights reserved.

关键词： Correlators

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HIGH-SPEED DROPLET SQUEEZING FOR T-CELL engineering 25

HIGH-SPEED DROPLET SQUEEZING FOR T-CELL ENGINEERING

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25th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2021

作者： Kim, You-Jeong Lee, Ha-Sung Chung, Aram Department of Chemical and Biological Engineering Sookmyung Women's University Seoul Korea Republic of School of Biomedical Engineering Korea University Seoul Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Korea Republic of

ISBN: (纸本)9781733419031

A novel droplet-based intracellular delivery platform is presented leveraging droplet microfluidics with mechanical cell permeabilization. A single cell and cargos were encapsulated in a droplet using a flow focusing device. Then, the droplet was accelerated by the sheath flow and passed through a single constriction at high speed, creating membrane discontinuities that facilitate the convective transport of biomolecules into the cell. Using this principle, the cell mechanoporation was achieved in a controlled and reproducible manner, allowing highly efficient, and dosage-controllable with substantially lower analyte amounts. The approach also enables vector-free delivery while maintaining high cell integrity without channel clogging. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Cell engineering

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Brain Function Analysis Using EEG Evidence: New Insights into English Paper-Based Versus Computer-Based Tests 16

Brain Function Analysis Using EEG Evidence: New Insights int...

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16th biomedical engineering International Conference, BMEiCON 2024

作者： Khemanuwong, Thapanee Angsuwatanakul, Thanate Phairot, Ekkapon Iramina, Keiji Puttasakul, Tasawan Bunyarit, Nagorn School of Liberal Arts King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand College of Biomedical Engineering Rangsit University Pathum Thani Thailand Songkhla Rajabhat University Faculty of Education Songkhla Thailand Graduate School of Systems Life Sciences School of Interdisciplinary Science and Innovation Kyushu University Fukuoka Japan College of Innovation and Industrial Management King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (纸本)9798331505431

In today's disruptive era, where digital systems and the internet are central, assessment methods are transitioning from paper-based to computer-based tests. As digital technology becomes more accessible, there is growing interest in determining whether these new formats provide more effective means of evaluating learning outcomes. To investigate this, we examined performance and objective measures of brain function during both computer-based and paper-based reading comprehension tests. This study focuses on brain function analysis of computer-based and paper-based tests measured by EEG signals. Five healthy students at the Bl CEFR level voluntarily participated in two experimental conditions: paper-based testing (PBT) and computer-based testing (CBT). During the tests, EEG signals were recorded and analyzed using MATLAB to identify various features of brain activity. The results indicate that participants who performed better on paper-based tests showed greater familiarity with the test format. The power spectral density of EEG recordings, along with the average frequency of alpha and beta waves, were positively correlated with test familiarity. Specifically, the correlation coefficients were as follows: CBT-difficult (r=0.82, p © 2024 IEEE.

关键词： Power spectral density

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