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Simulation of arrow-shaped micromixer with obstacles in blood plasma mixing

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AIP Conference Proceedings 2024年第1期3080卷

作者： Ziyan Muhammad Aqsha Basari Mohammad Akita Indianto Ridho Irwansyah Muhammad Satrio Utomo Siti Fauziyah Rahman Biomedical Engineering Study Program Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Energy Systems Engineering Graduate Program Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Department of Mechanical Engineering Faculty of Engineering Universitas Indonesia Kampus UI Depok West Java 16424 Indonesia Research Center for Metallurgy National Research and Innovation Agency Komplek PUSPIPTEK Setu Tangerang Selatan Banten 15314 Indonesia

In recent years, several applications of micromixers have been reported to have a number of advantages, including the use of small amounts of plasma, short reaction times, and good reaction efficiency. The samples analyzed in this study were blood plasma and distilled water. The process is carried out by passive mixing which is based on a microchannel structure to enhance the diffusion of molecules for efficient mixing. The arrow shape was chosen as the micromixer design because it has a better blending performance than the T and Y shapes. The types of obstacles also used to improve the mixing process. The simulation was carried out on COMSOL Multiphysics software version 5.6. The results showed better mixing results for the micromixer design with triangle right facing obstacles with the highest Reynolds number was 9.4326. Then followed by ellips obstacles with a value of 9.4322, then without obstacles that is 9.4309, after that the triangle left facing with a value of 9.4006, and finally the lowest Reynolds number is a design with a diamond obstacles of 9.2514.

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CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods

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arXiv 2023年

作者： Piovesan, Damiano Zago, Davide Joshi, Parnal Clara De Paolis Kaluza, M. Mehdiabadi, Mahta Ramola, Rashika Monzon, Alexander Miguel Reade, Walter Friedberg, Iddo Radivojac, Predrag Tosatto, Silvio C.E. Department of Biomedical Sciences University of Padova Padova35121 Italy Program in Bioinformatics and Computational Biology Iowa State University AmesIA50011 United States Department of Veterinary Microbiology and Preventive Medicine Iowa State University AmesIA50011 United States Khoury College of Computer Sciences Northeastern University BostonMA02115 United States Department of Information Engineering University of Padova Padova35121 Italy Kaggle San FranciscoCA United States

We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software. © 2023, CC BY.

关键词： Python

3D imaging lipidometry in single cell by in-flow holographic tomography

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Opto-Electronic Advances 2023年第1期6卷 10-25页

作者： Daniele Pirone Daniele Sirico Lisa Miccio Vittorio Bianco Martina Mugnano Danila del Giudice Gianandrea Pasquinelli Sabrina Valente Silvia Lemma Luisa Iommarini Ivana Kurelac Pasquale Memmolo Pietro Ferraro CNR-ISASI Institute of Applied Sciences and Intelligent Systems“E.Caianiello”Via Campi Flegrei 34PozzuoliNapoli 80078Italy Department of Electrical Engineering and Information Technologies University of Naples“FedericoⅡ”via Claudio 21Napoli 80125Italy Department of Chemical Materials and Production Engineering of the University of Naples FedericoⅡPiazzale Tecchio 80Napoli 80125Italy Department of Mathematics and Physics University of Campania“Luigi Vanvitelli”Caserta 81100Italy Biotechnology and Methods in Laboratory Medicine Department of ExperimentalDiagnostic and Specialty Medicine(DIMES)University of BolognaBologna 40126Italy Subcellular Nephro-Vascular Diagnostic Program Pathology Unit S.Orsola IRCCSUniversity of BolognaBologna 40126Italy Unit of Medical Genetics Department of Medical and Surgical Sciences(DIMEC)University of BolognaVia Massarenti 9Bologna 40138Italy Study and Research Center on Gynecological Neoplasias Department of Medical and Surgical Sciences(DIMEC)University of BolognaVia Massarenti 9Bologna 40138Italy Center for Applied Biomedical Research(CRBA) University of BolognaBologna 40138Italy Department of Pharmacy and Biotechnology(FABIT) University of BolognaBologna 40126Italy

The most recent discoveries in the biochemical field are highlighting the increasingly important role of lipid droplets(LDs)in several regulatory mechanisms in living *** are dynamic organelles and therefore their complete characterization in terms of number,size,spatial positioning and relative distribution in the cell volume can shed light on the roles played by *** now,fluorescence microscopy and transmission electron microscopy are assessed as the gold standard methods for identifying LDs due to their high sensitivity and ***,such methods generally only provide 2D assays and partial ***,both can be destructive and with low productivity,thus limiting analysis of large cell numbers in a *** we demonstrate for the first time the capability of 3D visualization and the full LD characterization in high-throughput with a tomographic phase-contrast flow-cytometer,by using ovarian cancer cells and monocyte cell lines as models.A strategy for retrieving significant parameters on spatial correlations and LD 3D positioning inside each cell volume is *** information gathered by this new method could allow more in depth understanding and lead to new discoveries on how LDs are correlated to cellular functions.

关键词： lipid droplets label-free phase-contrast imaging in-flow tomography 3D imaging

Utilizing probabilistic entanglement between sensors in quantum networks

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arXiv 2024年

作者： Van Milligen, Emily A. Gagatsos, Christos N. Kaur, Eneet Towsley, Don Guha, Saikat Department of Physics The University of Arizona 1630 East University Boulevard TucsonAZ85721 United States Department of Electrical and Computer Engineering The University of Arizona 1630 East University Boulevard TucsonAZ85721 United States Wyant College of Optical Sciences The University of Arizona 1630 East University Boulevard TucsonAZ85721 United States Program in Applied Mathematics The University of Arizona TucsonAZ85721 United States Cisco Quantum Lab Los Angeles United States College of Computer Science University of Massachusetts AmherstMA United States

One of the most promising applications of quantum networks is entanglement assisted sensing. The field of quantum metrology exploits quantum correlations to improve the precision bound for applications such as precision timekeeping, field sensing, and biological imaging. When measuring multiple spatially distributed parameters, current literature focuses on quantum entanglement in the discrete variable case—and quantum squeezing in the continuous variable case distributed amongst all of the sensors in a given network. However, it can be difficult to ensure all sensors pre-share entanglement of sufficiently high fidelity. This work probes the space between fully entangled and fully classical sensing networks by modeling a star network with probabilistic entanglement generation that is attempting to estimate the average of local parameters. The quantum Fisher information is used to determine which protocols best utilize entanglement as a resource for different network conditions. It is shown that without entanglement distillation there is a threshold fidelity below which classical sensing is preferable. For a network with a given number of sensors and links characterized by a certain initial fidelity and probability of success, this work outlines when and how to use entanglement, when to store it, and when it needs to be distilled. © 2024, CC BY.

关键词： Quantum entanglement

IPMN RISK ASSESSMENT UNDER FEDERATED LEARNING PARADIGM

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arXiv 2024年

作者： Pan, Hongyi Hong, Ziliang Durak, Gorkem Keles, Elif Aktas, Halil Ertugrul Taktak, Yavuz Medetalibeyoglu, Alpay Zhang, Zheyuan Velichko, Yury Spampinato, Concetto Schoots, Ivo Bruno, Marco J. Tiwari, Pallavi Bolan, Candice Gonda, Tamas Miller, Frank Keswani, Rajesh N. Wallace, Michael B. Xu, Ziyue Bagci, Ulas Department of Radiology Northwestern University ChicagoIL United States Department of Radiology Istanbul Faculty of Medicine Istanbul University Istanbul Turkey Department of Internal Medicine Istanbul Faculty of Medicine Istanbul University Istanbul Turkey Department of Electrical Electronic and Computer Engineering University of Catania Catania Italy Department of Radiology and Nuclear Medicine Erasmus Medical Center Rotterdam Netherlands Department of Gastroenterology and Hepatology Erasmus Medical Center Rotterdam Netherlands Department of Biomedical Engineering and Radiology University of Wisconsin MadisonWI United States Division of Gastroenterology and Hepatology Mayo Clinic JacksonvilleFL United States Division of Gastroenterology and Hepatology New York University New YorkNY United States Department of Gastroenterology and Hepatology Northwestern University ChicagoIL United States NVIDIA BethesdaMD United States

Accurate classification of Intraductal Papillary Mucinous Neoplasms (IPMN) is essential for identifying high-risk cases that require timely intervention. In this study, we develop a federated learning framework for multi-center IPMN classification utilizing a comprehensive pancreas MRI dataset. This dataset includes 652 T1-weighted and 655 T2-weighted MRI images, accompanied by corresponding IPMN risk scores from 7 leading medical institutions, making it the largest and most diverse dataset for IPMN classification to date. We assess the performance of DenseNet-121 in both centralized and federated settings for training on distributed data. Our results demonstrate that the federated learning approach achieves high classification accuracy comparable to centralized learning while ensuring data privacy across institutions. This work marks a significant advancement in collaborative IPMN classification, facilitating secure and high-accuracy model training across multiple centers. © 2024, CC BY.

关键词： Federated learning

A robust and interpretable deep learning framework for multi-modal registration via keypoints

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arXiv 2023年

作者： Wang, Alan Q. Yu, Evan M. Dalca, Adrian V. Sabuncu, Mert R. School of Electrical and Computer Engineering Cornell University Cornell Tech New YorkNY10044 United States Department of Radiology Weill Cornell Medical School New YorkNY10065 United States Iterative Scopes CambridgeMA02139 United States Computer Science and Artificial Intelligence Lab The Massachusetts Institute of Technology CambridgeMA02139 United States A.A. Martinos Center for Biomedical Imaging The Massachusetts General Hospital CharlestownMA02129 United States

We present KeyMorph, a deep learning-based image registration framework that relies on automatically detecting corresponding keypoints. State-of-the-art deep learning methods for registration often are not robust to large misalignments, are not interpretable, and do not incorporate the symmetries of the problem. In addition, most models produce only a single prediction at test-time. Our core insight which addresses these shortcomings is that corresponding keypoints between images can be used to obtain the optimal transformation via a differentiable closed-form expression. We use this observation to drive the end-to-end learning of keypoints tailored for the registration task, and without knowledge of ground-truth keypoints. This framework not only leads to substantially more robust registration but also yields better interpretability, since the keypoints reveal which parts of the image are driving the final alignment. Moreover, KeyMorph can be designed to be equivariant under image translations and/or symmetric with respect to the input image ordering. Finally, we show how multiple deformation fields can be computed efficiently and in closed-form at test time corresponding to different transformation variants. We demonstrate the proposed framework in solving 3D affine and spline-based registration of multi-modal brain MRI scans. In particular, we show registration accuracy that surpasses current state-of-the-art methods, especially in the context of large displacements. Our code is available at https://***/alanqrwang/keymorph. © 2023, CC0.

关键词： Image registration

Multifunctional Microcoaxial Fibers for Electrochemical, Optical and Spectroelectrochemical Sensing

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SSRN

SSRN 2022年

作者： Shi, Yuesong Ward, Spencer Riley, Conor Sirbuly, Donald J. Materials Science and Engineering Program University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Nanoengineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States

Developing microdevices capable of performing multifunctional sensing measurements is of grand importance for various applications including the study of diseases, rapid biomolecular detection, and drug discovery. In this paper, we demonstrate a compact electro-optical multimodal microprobe with a small footprint (~10 µm diameter), low electrical impedance (~ 10 kΩ at 1 kHz), and high optical spatial resolution. The electrical channel is validated by selectively detecting dopamine and serotonin via electrochemistry with a limit of detection of 800 nM and 1.2 μM, respectively. The optical channel is then combined with the adjacent electrical channel to perform localized spectroelectrochemical probing of electrochromic materials including conductive polymers such as poly(3,4-ethylenedioxythiophene) and thiazine dyes such as methylene blue. Due to the size of the probe, dimensional and mechanical tunability, and minimal interference between the co-localized electrical and optical channels, this device architecture shows great promise for in vivo sensing and in situ biomolecular measurements. © 2022, The Authors. All rights reserved.

关键词： Amines

Bioactive Glass Preloaded with Antibiotics for Delivery of Long-Term Localized Drug Release Exhibiting Inherent Antimicrobial Activity

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Applied Sciences 2025年第10期15卷 5363-5363页

作者： Dana Almasri Yaser Dahman Department of Electrical Computer & Biomedical Engineering Toronto Metropolitan University Toronto ON M5B 2K3 Canada Department of Chemical Engineering Toronto Metropolitan University Toronto ON M5B 2K3 Canada

Bacterial infections caused by biofilms are often difficult to treat due to the resistant nature of the latter, which require high concentrations of antibiotics to be applied for prolonged periods to achieve complete eradication. This study aimed to design a new drug delivery system for long-term drug release for the treatment of bacterial infections. Specifically, bioactive glass preloaded with vancomycin (BG-V) and synthesized without any thermal treatment was designed to load higher percentages of the drug and release it slowly over time. In this study, BG-V was-synthesized using a solution containing vancomycin, with glass being formed around it by adding metal precursors to this solution. The BG-V was then left to dry at room temperature to form a white powder with vancomycin trapped in the structure. The successful synthesis of BG-V was confirmed by X-ray diffraction, Fourier-transform infrared spectroscopy, scanning emission microscopy, and nitrogen adsorption–desorption analysis. The results showed that BG-V was successfully developed using FTIR, showing vancomycin within the BG-V structure. After the drug release, BG-V showed great bioactivity, as indicated by the XRD and bacterial studies. The result shows that drug release is controlled by a combination of diffusion through the matrix and the gradual erosion of the delivery system.

关键词： bioactive glass vancomycin drug delivery release kinetics antimicrobial test sol–gel synthesis

Raman Spectroscopy Reveals Photobiomodulation-Induced α-Helix to β-Sheet Transition in Tubulins: Potential Implications for Alzheimer's and Other Neurodegenerative Diseases

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arXiv 2023年

作者： Di Gregorio, Elisabetta Staelens, Michael Hosseinkhah, Nazanin Karimpoor, Mahroo Liburd, Janine Lim, Lew Shankar, Karthik Tuszyński, Jack A. Department of Physics Faculty of Science University of Alberta EdmontonABT6G 2E1 Canada Faculty of Biomedical Engineering Polytechnic University of Turin Turin10129 Italy Department of Physics Freie Universität Berlin Berlin14195 Germany Instituto de Física Corpuscular CSIC Universitat de València Carrer Catedràtic José Beltrán 2 València Paterna46980 Spain Vielight Inc. TorontoONM4Y 2G8 Canada Department of Electrical and Computer Engineering Faculty of Engineering University of Alberta EdmontonABT6G 1H9 Canada Department of Data Science and Engineering Silesian University of Technology Gliwice44-100 Poland

In small clinical studies, the application of photobiomodulation (PBM), which typically delivers near-infrared (NIR) to treat the brain, has presented some remarkable results in the treatment of dementia and several neurodegenerative diseases. However, while the literature is rich with the mechanisms of action underlying PBM outcomes, the underlying mechanisms affecting a neurodegenerative disease are not entirely clear. While large clinical trials are warranted to validate these findings, evidence of the mechanisms can explain and hence provide credible support for PBM as a potential treatment for these diseases. Tubulin and its polymerized state of microtubules have been known to play important roles in the pathology of Alzheimer's and other neurodegenerative diseases. We investigated the effects of PBM on these structures in the quest for answers. In this study, we employed a Raman spectroscopic analysis of the amide I band of polymerized samples of tubulin exposed to pulsed low-intensity NIR radiation (810 nm, 10 Hz, 22.5 J/cm2 dose). Peaks in the Raman fingerprint region (300-1900 cm−1), in particular, in the amide I band (1600-1700 cm−1), can be used to quantify the percentage of protein secondary structures. Under this band, hidden signals of C=O stretching, belonging to different structures, are superimposed-producing a complex signal as a result. An accurate decomposition of the amide I band is therefore required for the reliable analysis of the conformation of proteins, which we achieved through a straightforward method employing a Voigt profile. This approach was validated through secondary structure analyses of unexposed control samples, for which comparisons with other values available in the literature could be conducted. Subsequently, using this validated method, we present novel findings of statistically significant alterations in the secondary structures of NIR-exposed tubulin, characterized by a notable decrease in α-helix content and a concurrent

关键词： Neurodegenerative diseases