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arXiv 2025年

作者： Hou, Qingshan Zhou, Yukun Goh, Jocelyn Hui Lin Zou, Ke Yew, Samantha Min Er Srinivasan, Sahana Wang, Meng Lo, Thaddaeus Lei, Xiaofeng Wagner, Siegfried K. Chia, Mark A. Yang, Dawei Jiang, Hongyang Ran, AnRan Santos, Rui Somfai, Gabor Mark Zhou, Juan Helen Chen, Haoyu Chen, Qingyu Cheung, Carol Yim-Lui Keane, Pearse A. Tham, Yih Chung Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore School of Computer Science and Engineering Northeastern University Shenyang China Centre for Innovation and Precision Eye Health Yong Loo Lin School of Medicine National University of Singapore Singapore Centre for Medical Image Computing University College London London United Kingdom NIHR Biomedical Research Centre Moorfields Eye Hospital NHS Foundation Trust London United Kingdom Department of Medical Physics and Biomedical Engineering University College London London United Kingdom Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Singapore Institute of Ophthalmology University College London London United Kingdom Department of Ophthalmology and Visual Sciences Chinese University of Hong Kong Hong Kong Department of Ophthalmology Stadtspital Zürich Zurich Switzerland Spross Research Institute Zurich Switzerland Department of Ophthalmology Semmelweis University Budapest Hungary Centre for Sleep and Cognition Centre for Translational MR Research Yong Loo Lin School of Medicine National University of Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore Joint Shantou International Eye Center Shantou University the Chinese University of Hong Kong Guangdong Shantou China Shantou University Medical College Guangdong Shantou China Department of Biomedical Informatics and Data Science Yale School of Medicine Yale University New Haven United States Duke-NUS Medical School Singapore

The advent of foundation models (FMs) is transforming medical domain. In ophthalmology, RETFound, a retina-specific FM pre-trained sequentially on 1.4 million natural images and 1.6 million retinal images, has demonstrated high adaptability across clinical applications. Conversely, DINOv2, a general-purpose vision FM pre-trained on 142 million natural images, has shown promise in non-medical domains. However, its applicability to clinical tasks remains underexplored. To address this, we conducted head-to-head evaluations by finetuning RETFound and three DINOv2 models (large, base, small) for ocular disease detection and systemic disease prediction tasks, across eight standardized open-source ocular datasets, as well as the Moorfields AlzEye and the UK Biobank datasets. DINOv2-large model outperformed RETFound in detecting diabetic retinopathy (AUROC=0.850–0.952 vs. 0.823-0.944, across three datasets, all P≤0.007) and multi-class eye diseases (AUROC=0.892 vs. 0.846, P Copyright © 2025, The Authors. All rights reserved.

关键词： Ophthalmology

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Detection of SARS-CoV-2 Viral Particles Using Direct, Reagent-Free Electrochemical Sensing

Detection of SARS-CoV-2 Viral Particles Using Direct, Reagen...

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2023 AIChE Annual Meeting

作者： Yousefi, Hanie Mahmud, Alam Chang, Dingran Das, Jagotamoy Gomis, Surath Chen, Jenise B. Wang, Hansen Been, Terek Yip, Lily Coomes, Eric Li, Zhijie Mubareka, Samira McGeer, Allison Christie, Natasha Gray-Owen, Scott Cochrane, Alan Rini, James M. Sargent, Edward H. Kelley, Shana O. Leslie Dan Faculty of Pharmacy University of Toronto TorontoONM5S 3M2 Canada Department of Chemistry Department of Biochemistry Institute of Biomaterials and Biomedical Engineering University of Toronto TorontoONM5S 3H6 Canada Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3G4 Canada Department of Chemistry University of Toronto TorontoONM5S 3H6 Canada Sunnybrook Research Institute TorontoONM4N 3N5 Canada Division of Infectious Disease Department of Medicine University of Toronto TorontoONM5G 2C4 Canada Department of Microbiology Sinai Health System TorontoONM5G 1X5 Canada Combined Containment Level 3 Unit University of Toronto TorontoONM5S 1A8 Canada Department of Molecular Genetics and Combined Containment Level 3 Unit University of Toronto TorontoONM5S 1A8 Canada Department of Molecular Genetics Department of Biochemistry University of Toronto TorontoONM5S 1A8 Canada

The development of new methods for direct viral detection using streamlined and ideally reagent-free assays is a timely and important, but challenging, problem. The challenge of combatting the COVID-19 pandemic has been exacerbated by the lack of rapid and effective methods to identify viral pathogens like SARS-CoV-2 on-demand. Existing gold standard nucleic acid-based approaches require enzymatic amplification to achieve clinically relevant levels of sensitivity and are not typically used outside of a laboratory setting. Here, we report reagent-free viral sensing that directly reads out the presence of viral particles in 5 minutes using only a sensor-modified electrode chip. The approach relies on a class of electrode-tethered sensors bearing an analyte-binding antibody displayed on a negatively charged DNA linker that also features a tethered redox probe. When a positive potential is applied, the sensor is transported to the electrode surface. Using chronoamperometry, the presence of viral particles and proteins can be detected as these species increase the hydrodynamic drag on the sensor. This report is the first virus-detecting assay that uses the kinetic response of a probe/virus complex to analyze the complexation state of the antibody. We demonstrate the performance of this sensing approach as a means to detect, within 5 min, the presence of the SARS-CoV-2 virus and its associated spike protein in test samples and in unprocessed patient saliva. © 2021 American Chemical Society.

关键词： Coronavirus

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Can large language models provide useful feedback on research papers? A large-scale empirical analysis

arXiv

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arXiv 2023年

作者： Liang, Weixin Zhang, Yuhui Cao, Hancheng Wang, Binglu Ding, Daisy Yi Yang, Xinyu Vodrahalli, Kailas He, Siyu Smith, Daniel Scott Yin, Yian McFarland, Daniel A. Zou, James Department of Computer Science Stanford University StanfordCA94305 United States Kellogg School of Management Northwestern University EvanstonIL60208 United States Department of Biomedical Data Science Stanford University StanfordCA94305 United States Department of Information Science Cornell University IthacaNY14850 United States Department of Electrical Engineering Stanford University StanfordCA94305 United States Graduate School of Education Stanford University StanfordCA94305 United States

Expert feedback lays the foundation of rigorous research. However, the rapid growth of scholarly production and intricate knowledge specialization challenge the conventional scientific feedback mechanisms. High-quality peer reviews are increasingly difficult to obtain. Researchers who are more junior or from under-resourced settings have especially hard times getting timely feedback. With the breakthrough of large language models (LLM) such as GPT-4, there is growing interest in using LLMs to generate scientific feedback on research manuscripts. However, the utility of LLM-generated feedback has not been systematically studied. To address this gap, we created an automated pipeline using GPT-4 to provide comments on the full PDFs of scientific papers. We evaluated the quality of GPT-4’s feedback through two large-scale studies. We first quantitatively compared GPT-4’s generated feedback with human peer reviewer feedback in 15 Nature family journals (3,096 papers in total) and the ICLR machine learning conference (1,709 papers). The overlap in the points raised by GPT-4 and by human reviewers (average overlap 30.85% for Nature journals, 39.23% for ICLR) is comparable to the overlap between two human reviewers (average overlap 28.58% for Nature journals, 35.25% for ICLR). The overlap between GPT-4 and human reviewers is larger for the weaker papers (i.e., rejected ICLR papers;average overlap 43.80%). We then conducted a prospective user study with 308 researchers from 110 US institutions in the field of AI and computational biology to understand how researchers perceive feedback generated by our GPT-4 system on their own papers. Overall, more than half (57.4%) of the users found GPT-4 generated feedback helpful/very helpful and 82.4% found it more beneficial than feedback from at least some human reviewers. While our findings show that LLM-generated feedback can help researchers, we also identify several limitations. For example, GPT-4 tends to focus on certain aspects

关键词： Quality control

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Performance analysis of multi-reconfigurable intelligent surface-empowered THz wireless systems

arXiv

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arXiv 2022年

作者： Boulogeorgos, Alexandros-Apostolos A. Chatzidiamantis, Nestor Sandalidis, Harilaos G. Alexiou, Angeliki Di Renzo, Marco Digital Systems University Of Piraeus Piraeus18534 Greece Department Of Electrical And Computer Engineering Aristotle University Of Thessaloniki Thessaloniki54124 Greece Department Of Computer Science And Biomedical Informatics University Of Thessaly Lamia35131 Greece Université Paris-Saclay CNRS CentraleSupélec Laboratoire Des Signaux Et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France

In this paper, we introduce a theoretical framework for analyzing the performance of multi-reconfigurable intelligence surface (RIS) empowered terahertz (THz) wireless systems subject to turbulence and stochastic beam misalignment. In more detail, we extract a closed-form expression for the outage probability that quantifies the joint impact of turbulence and misalignment as well as the effect of transceivers' hardware imperfections. Our results highlight the importance of accurately modeling both turbulence and misalignment when assessing the performance of multi-RIS-empowered THz wireless systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Alignment

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Cell Alignment Modulated by Surface Nano-Topography – Roles of Cell-Matrix and Cell-Cell Interactions

SSRN

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SSRN 2021年

作者： Coyle, Stephen Doss, Bryant Huo, Yucheng Singh, Hemang Raj Quinn, David Hsia, K. Jimmy LeDuc, Philip R. Department of Mechanical Engineering Carnegie Mellon University PittsburghPA United States School of Mechanical & Aerospace Engineering Nanyang Technological University Singapore School of Chemical & Biomedical Engineering Nanyang Technological University Singapore Department of Biomedical Engineering Carnegie Mellon University PittsburghPA United States Department of Biological Sciences Carnegie Mellon University PittsburghPA United States Department of Computational Biology Carnegie Mellon University PittsburghPA United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States

Cell alignment is critical in numerous areas, from tissue engineering to biohybrid robotics. Cell alignment is modulated through many features including surface topographies, mechanical cues from cell-matrix interactions, and cell-cell interactions. In this study, we present our approach to examine the role of surface topographies and cell-cell interactions with respect to cell alignment. We developed an approach to create wavy surface topographies at the nanometer size scale, which when integrated with cell culture affects cell alignment. Within a defined range of wavelengths and amplitudes of the surface topographies, cell alignment is dependent on culture confluency. This cell alignment’s dependence on confluency suggests that cell-cell interactions related to alignment may be correlated to cell-matrix interactions. Thus, we inhibited N-cadherin related cell-cell interactions through introduced anti-N-cadherin while culturing cells on our controlled surface topographies. We found that when using anti-N-cadherin, cells on patterned surfaces required greater confluency to achieve the same alignment to cell culture not in the presence of the antibody. Our results will be important in numerous areas including tissue repair, cell differentiation, and biohybrid systems. © 2021, The Authors. All rights reserved.

关键词： Topography

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Integrated sensing and delivery of oxygen for next- generation smart wound dressings

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Microsystems & Nanoengineering 2020年第1期6卷 991-1006页

作者： Manuel Ochoa Rahim Rahimi Jiawei Zhou Hongjie Jiang Chang Keun Yoon Dinesh Maddipatla Binu Baby Narakathu Vaibhav Jain Mark Michael Oscai Thaddeus Joseph Morken Rebeca Hannah Oliveira Gonzalo L.Campana Oscar W.Cummings Michael A.Zieger Rajiv Sood Massood Z.Atashbar Babak Ziaie School of Electrical and Computer Engineering Purdue UniversityWest Lafayette 47907 INUSA Birck Nanotechnololgy Center 1205W State StreetWest Lafayette 47907 INUSA School of Material Science Engineering Purdue UniversityWest Lafayette 47907 INUSA Electrical and Computer Engineering Department Western Michigan University4601 Campus Drive B-236Kalamazoo 49008 MIUSA School of Mechanical Engineering Purdue UniversityWest Lafayette 47907 INUSA Indiana University School of Medicine 980 West Walnut StreetBuilding R3 Room C634Indianapolis 46202 INUSA Department of Pathology and Laboratory Medicine Indiana University School of MedicineIU Health Pathology Laboratory350W 11th StreetRoom 4054IndianapolisIN 46202USA Weldon School of Biomedical Engineering Purdue UniversityWest Lafayette 47907 INUSA Present address:Shenzhen MSU-BIT University ShenzhenChina

Chronic wounds affect over 6.5 million Americans and are notoriously difficult to *** oxygenation of the wound bed is one of the most critical and treatable wound management factors,but existing oxygenation systems do not enable concurrent measurement and delivery of oxygen in a convenient wearable ***,we developed a low-cost alternative for continuous O 2 delivery and sensing comprising of an inexpensive,paper-based,biocompatible,flexible platform for locally generating and measuring oxygen in a wound *** platform takes advantage of recent developments in the fabrication of flexible microsystems including the incorporation of paper as a substrate and the use of a scalable manufacturing technology,inkjet ***,we demonstrate the functionality of the oxygenation patch,capable of increasing oxygen concentration in a gel substrate by 13%(5ppm)in *** platform is able to sense oxygen in a range of 5–26 *** vivo studies demonstrate the biocompatibility of the patch and its ability to double or triple the oxygen level in the wound bed to clinically relevant levels.

关键词： patch smart printing

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Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images

arXiv

引用

arXiv 2021年

作者： Sharifrazi, Danial Alizadehsani, Roohallah Roshanzamir, Mohamad Joloudari, Javad Hassannataj Shoeibi, Afshin Jafari, Mahboobeh Hussain, Sadiq Sani, Zahra Alizadeh Hasanzadeh, Fereshteh Khozeimeh, Fahime Khosravi, Abbas Nahavandi, Saeid Panahiazar, Maryam Zare, Assef Shariful Islam, Sheikh Mohammed Rajendra, U. Acharya Department of Computer Engineering School of Technical and Engineering Shiraz Branch Islamic Azad University Shiraz Iran Deakin University Geelong Australia Department of Engineering Fasa Branch Islamic Azad University Post Box No 364 Fasa Fars*** Iran Department of Computer Engineering Faculty of Engineering University of Birjand Birjand Iran Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran Faculty of Electrical and Computer Engineering Biomedical Data Acquisition Lab K. N. Toosi University of Technology Tehran Iran Electrical and Computer Engineering Faculty Semnan University Semnan Iran System Administrator Dibrugarh University Assam786004 India Rajaie Cardiovascular Medical and Research Center Iran University of Medical Sciences Tehran Iran Omid hospital Iran University of Medical Sciences Tehran Iran Institute for Computational Health Sciences University of California San Francisco United States Faculty of Electrical Engineering Gonabad Branch Islamic Azad University Gonabad Iran Institute for Physical Activity and Nutrition Deakin University Melbourne Australia Cardiovascular Division The George Institute for Global Health Australia Sydney Medical School University of Sydney Australia Department of Electronics and Computer Engineering Ngee Ann Polytechnic Singapore Department of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore Department of Bioinformatics and Medical Engineering Asia University Taiwan

The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to prevent secondary infections and its spread from one person to another. Therefore, it is essential to use an automatic diagnosis system along with clinical procedures for the rapid diagnosis of COVID-19 to prevent its spread. Artificial intelligence techniques using computed tomography (CT) images of the lungs and chest radiography have the potential to obtain high diagnostic performance for Covid-19 diagnosis. In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images. A new X-ray image dataset was collected and subjected to high pass filter using a Sobel filter to obtain the edges of the images. Then these images are fed to CNN deep learning model followed by SVM classifier with ten-fold cross validation strategy. This method is designed so that it can learn with not many data. Our results show that the proposed CNN-SVM with Sobel filtering (CNN-SVM+Sobel) achieved the highest classification accuracy of 99.02% in accurate detection of COVID-19. It showed that using Sobel filter can improve the performance of CNN. Unlike most of the other researches, this method does not use a pre-trained network. We have also validated our developed model using six public databases and obtained the highest performance. Hence, our developed model is ready for clinical application. Copyright © 2021, The Authors. All rights reserved.

关键词： Data mining

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Comb-calibrated Raman Spectroscopy of Molecular Hydrogen

Comb-calibrated Raman Spectroscopy of Molecular Hydrogen

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Marco Lamperti Lucile Rutkowski Daniele Ronchetti Davide Gatti Riccardo Gotti Giulio Cerullo Franck Thibault Hubert Jóźwiak Szymon Wójtewicz Piotr Masłowski Piotr Wcisło Dario Polli Marco Marangoni Dipartimento di Fisica Politecnico di Milano and IFN-CNR Lecco Italy Department of Science and High Technology University of Insubria Como Italy Univ Rennes CNRS IPR (Institut de Physique de Rennes)-UMR 6251 Rennes France Department of Electrical Computer and Biomedical Engineering Universitá degli studi di Pavia Pavia Italy Faculty of Physics Institute of Physics Astronomy and Informatics Nicolaus Copernicus University Torun Poland

ISBN: (纸本)9798350345995

Molecular hydrogen and its isotopologues are key systems to test quantum electrodynamics (QED) at molecular length scales, as their energy levels can be calculated with high accuracy[1]. Comparison of the theoretical values with highly accurate experimental determinations of transition frequencies allows one to test QED and theories beyond the standard model of particle physics[2]. Recent accurate measurements of rovibrational frequencies of HD and D2, covering mostly the second overtone band, have shown a systematic deviation between measured and calculated transition frequencies. Yet, available measurements on H2 are characterized by uncertainties one order of magnitude larger than theory.

关键词： Frequency combs Frequency measurement Hydrogen Molecular spectroscopy Quantum electrodynamics Raman spectroscopy

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Effect of alginate and chitosan addition in the fabrication of polyvinyl alcohol-based matrix for tissue engineering applications

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AIP Conference Proceedings 2024年第1期3215卷

作者： Retno Wahyu Nurhayati Fatimah Azzahra Nuzli Fahdia Mazfufah Siti Fauziyah Rahman Wildan Mubarok Department of Chemical Engineering Faculty of Engineering Universitas Indonesia 16464 Depok Indonesia Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia 16464 Depok Indonesia Stem Cells & Tissue Engineering Cluster Indonesian Medical Education and Research Institute Faculty of Medicine Universitas Indonesia Jakarta 10430 Indonesia Doctoral Program in Biomedical Sciences Faculty of Medicine Universitas Indonesia Jakarta 10430 Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Indonesia 16464 Depok Indonesia Division of Chemical Engineering Department of Materials Engineering Science Graduate School of Engineering Science Osaka University 560-0031 Toyonaka Japan

Recently, there has been a growing interest in artificial skin on hydrogels as a potential alternative for animal testing to evaluate the efficacy and safety of new drugs or cosmetics. Synthetic polymers have been widely used due to their superior physicochemical properties. However, synthetic polymers such as polyvinyl alcohol (PVA) are limited by their poor biocompatibility and cell adhesion. Combining synthetic and natural polymers can improve these properties. Therefore, in this study, we aimed to investigate the effect of alginate and chitosan addition to PVA-based hydrogels on protein adsorption, cell viability and cell attachment. The addition of chitosan decreased protein adsorption, which was caused by the changes in electrostatic charge by PVA-chitosan interaction and changes in surface roughness. Primary human fibroblast cells cultured on PVA, PVA-alginate and PVA-chitosan had >80% viability which indicates the cytocompatibility of the hydrogels. More importantly, alginate and chitosan also improved the cell attachment on the PVA-based hydrogels. Taken together, the addition of both alginate and chitosan has the potential to improve PVA-based hydrogels for artificial skin application.

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Transverse acoustic spin and torque from pure spinning of objects

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Physical Review B 2021年第6期104卷 L060104-L060104页

作者： M. Farhat P.-Y. Chen M. Amin A. Alù Y. Wu Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago Illinois 60607 USA College of Engineering Taibah University Madinah 42353 Saudi Arabia Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10016 USA

Acoustic spin has been recently explored for many applications. In particular, transverse acoustic spin was demonstrated for inhomogeneous acoustic fields. In this Letter, we show the emergence of acoustic spin and torque in rotating acoustic objects of the same physical properties as the surrounding, to single out the effects purely due to rotation. The spinning of a cylindrical column of air or water in the same medium possesses intrinsic spin angular momentum, and we study the torque and force it experiences in evanescent acoustic fields. The resulting discontinuity can thus scatter sound in unusual ways, including a negative radiation force, although it has no imaginary part in its parameters.

关键词： Acoustic interactions Acoustic metamaterials Acoustic wave phenomena Linear acoustics

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