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Measuring 3D Chemistry at 1 nm Resolution with Fused Multi-Modal Electron Tomography

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1394-1395页

作者： Schwartz, Jonathan Di, Zichao Wendy Jiang, Yi Cho, Min Gee Qian, Yiwen Gu, Junsi Rozeveld, Steve Ercius, Peter Fessler, Jeffrey A. Xu, Ting Scott, Mary Hovden, Robert Department of Materials Science and Engineering University of Michigan Ann Arbor MI United States Mathematics and Computer Science Division Argonne National Laboratory Lemont IL United States Advanced Photon Source Argonne National Laboratory Lemont IL United States Department of Materials Science and Engineering University of California at Berkeley Berkeley CA United States National Center for Electron Microscopy Lawrence Berkeley National Laboratory Berkeley CA United States Dow Chemical Co. Midland MI United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI United States Materials Science Division Lawrence Berkeley National Laboratory Berkeley CA United States Applied Physics Program University of Michigan Ann Arbor MI United States

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Complexity Analysis based on Parietal Fuzzy Entropy to Facilitate ADHD Diagnosis in Young Children 46

Complexity Analysis based on Parietal Fuzzy Entropy to Facil...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Huang, I-Wen Jheng, Yu-Ci Chen, I-Chun Ko, Li-Wei National Yang Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300040 Taiwan National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering Hsinchu300040 Taiwan National Yang Ming Chiao Tung University International Program in Interdisciplinary Neuroscience College of Biological Science and Technology Hsinchu300040 Taiwan Ton-Yen General Hospital Department of Physical Medicine and Rehabilitation Hsinchu302048 Taiwan Kaohsiung Medical University Drug Development and Value Creation Research Center Kaohsiung807378 Taiwan

ISBN: (纸本)9798350371499

Attention deficit hyperactivity disorder (ADHD) is the most common condition affecting the development of neurons in children. Therefore, early and accurate diagnosis of ADHD in young children is of paramount importance. In this study, the 8-channel wireless wearable EEG measurement device was employed to record EEG data from 30 children diagnosed with ADHD and 30 typical development (TD) young children aged 4-7 years. The data was collected both during rest and while the children performed a Kiddie Continuous Performance Test (K-CPT). We extract relative power spectral density (PSD) unaffected by factors like skull resistance and thickness. Additionally, a range of complex entropy values based on the time domain were extracted. These included sample entropy (SaEn), permutation entropy (PeEn), singular value decomposition entropy (SvdEn), and fuzzy entropy (FuEn). We compare the performance of k-Nearest Neighbors (kNN), Support Vector Machine (SVM), and XGBoost, and utilized the sequential forward selection (SFS) feature selection method in the wrapper approach. Through this process, the study identified the most effective EEG data segments and feature subsets. The findings indicated that using a combination of resting and K-CPT EEG data yielded greater discriminability. Notably, the study found that extracting beta power from the right occipital lobe along with fuzzy entropy from the parietal lobe resulted in optimal accuracy of 90% in distinguishing between children with ADHD and TD children. These outcomes highlight the potential of relative PSD and complexity metrics to support the clinical diagnosis of early ADHD. Furthermore, these metrics may contain unique neurobiomarkers that could be valuable for devising early intervention strategies. © 2024 IEEE.

关键词： Diseases

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Photonic axion insulator

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science (New York, N.Y.) 2025年第6730期387卷 162-166页

作者： Liu, Gui-Geng Mandal, Subhaskar Xi, Xiang Wang, Qiang Devescovi, Chiara Morales-Pérez, Antonio Wang, Ziyao Yang, Linyun Banerjee, Rimi Long, Yang Meng, Yan Zhou, Peiheng Gao, Zhen Chong, Yidong García-Etxarri, Aitzol Vergniory, Maia G. Zhang, Baile Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore Research Center for Industries of the Future Department of Electronic and Information Engineering School of Engineering Westlake University Hangzhou China School of Electrical Engineering and Intelligentization Dongguan University of Technology Dongguan China National Laboratory of Solid State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing China Donostia International Physics Center Donostia-San Sebastian Spain Institute for Theoretical Physics ETH Zurich Zurich Switzerland Material and Applied Physics Department University of the Basque Country (UPV/EHU) Donostia-San Sebastián Spain Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China National Engineering Research Center of Electromagnetic Radiation Control Materials Key Laboratory of Multi-spectral Absorbing Materials and Structures of Ministry of Education University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Optical Fiber and Cable Manufacture Technology Department of Electronic and Electrical Engineering Guangdong Key Laboratory of Integrated Optoelectronics Intellisense Southern University of Science and Technology Shenzhen China Centre for Disruptive Photonic Technologies Photonics Institute Nanyang Technological University Singapore IKERBASQUE Basque Foundation for Science Bilbao Spain Max Planck Institute for Chemical Physics of Solids Dresden Germany Département de Physique et Institut Quantique Université de Sherbrooke Sherbrooke Canada

Axions, hypothetical elementary particles that remain undetectable in nature, can arise as quasiparticles in three-dimensional crystals known as axion insulators. Previous implementations of axion insulators have largely been limited to two-dimensional systems, leaving their topological properties in three dimensions unexplored in experiment. Here, we realize an axion insulator in a three-dimensional photonic crystal and probe its topological properties. Demonstrated features include half-quantized Chern numbers on each surface that resembles a fractional Chern insulator, unidirectional chiral hinge states forming topological transport in three dimensions, and arithmetic operations between fractional and integer Chern numbers. Our work experimentally establishes the axion insulator as a three-dimensional topological phase of matter and enables chiral states to form complex, unidirectional three-dimensional networks through braiding.

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Natural rubber-based pressure sensitive adhesive as a drug carrier

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Materials Today: Proceedings 2023年 75卷 9-14页

作者： Puyathorn, Napaphol Limsirilak, Sasiprapa Pichayakorn, Wiwat Kalkornsurapranee, Ekwipoo Phaechamud, Thawatchai Program of Pharmaceutical Engineering Faculty of Pharmacy Silpakorn University Nakhon Pathom 73000 Thailand Faculty of Pharmacy Siam University Bangkok 10160 Thailand Department of Pharmaceutical Technology Faculty of Pharmaceutical Sciences Prince of Songkla University Songkhla 90110 Thailand Division of Physical Science Faculty of Science Prince of Songkla University Songkhla 90110 Thailand Department of Pharmaceutical Technology Faculty of Pharmacy Silpakorn University Nakhon Pathom 73000 Thailand Natural Bioactive and Material for Health Promotion and Drug Delivery System Group Faculty of Pharmacy Silpakorn University Nakhon Pathom 73000 Thailand

Natural rubber (NR) has been utilized in several products from its interesting unique properties. This study aimed to develop the pressure-sensitive adhesives (PSA) as the transdermal patches from NR by two-roll mill kneading technique. Hydroxyethyl cellulose (HEC) was blended as a tackifier agent. The propranolol HCl and ibuprofen at different parts per hundred of rubber (phr) were loaded into this developed PSA. The appearance, thickness, crystallinity, contact angle, water sorption and erosion, adhesion, and in vitro drug permeation of these patches were evaluated. The thickness of all patches was in the range of 0.46–1.07 mm. The drug-loaded patches showed diverse unique topographies depended on both type and amount of drug incorporation. From powder X-ray diffraction analysis, the plain NR-PSA showed the amorphous structure, while the halo pattern inserted with sharp drug peaks were observed on drug-loaded PSA. The contact angle of all samples was in the range of 80–90° indicating their hydrophobic surface. However, they displayed an increased % water sorption with the time of soaking. The 2–4 N adhesion force was evident for all fabricated drug-loaded PSAs. The propranolol HCl permeated from PSA notably lower than ibuprofen. The residual of the drugs in patches was about 85–90 %. These results provided the basic physicochemical properties for the further development of PSA as the transdermal patch. [copyright information to be updated in production process] © 2022

关键词： Adhesion

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Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation

arXiv

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arXiv 2024年

作者： Oh, Yeongtak Lee, Jonghyun Choi, Jooyoung Jung, Dahuin Hwang, Uiwon Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of School of Computer Science and Engineering Soongsil University Korea Republic of Division of Digital Healthcare Yonsei University Korea Republic of

Test-time adaptation (TTA) addresses the unforeseen distribution shifts occurring during test time. In TTA, performance, memory consumption, and time consumption are crucial considerations. A recent diffusion-based TTA approach for restoring corrupted images involves image-level updates. However, using pixel space diffusion significantly increases resource requirements compared to conventional model updating TTA approaches, revealing limitations as a TTA method. To address this, we propose a novel TTA method that leverages an image editing model based on a latent diffusion model (LDM) and fine-tunes it using our newly introduced corruption modeling scheme. This scheme enhances the robustness of the diffusion model against distribution shifts by creating (clean, corrupted) image pairs and fine-tuning the model to edit corrupted images into clean ones. Moreover, we introduce a distilled variant to accelerate the model for corruption editing using only 4 network function evaluations (NFEs). We extensively validated our method across various architectures and datasets including image and video domains. Our model achieves the best performance with a 100 times faster runtime than that of a diffusion-based baseline. Furthermore, it is three times faster than the previous model updating TTA method that utilizes data augmentation, making an image-level updating approach more feasible. ∗ © 2024, CC BY.

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Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 959-973页

作者： Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Department of Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Gene Regulation and Systems Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055China

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.

关键词： Transcription start site Machine learning Deep learning Meta-learning RNA sequencing

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Novel Dopamine-Derived Carbon Modified Fe-Based Metal-Organic Framework Enhanced Aptasensor Rendering Ultrasensitive Electrochemical Detection of Oxytetracycline

SSRN

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SSRN 2024年

作者： Song, Jialing Fan, Xiaoxuan Ee, Liang Ying Lin, Xuanhao Li, Sam Fong Yau Huang, Manhong Singapore Donghua University China Shanghai University College of Science Department of Chemistry International Joint Laboratory Catalyst Chemistry Shanghai200444 China College of Environmental Science and Engineering State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry Donghua University Shanghai201620 China National University of Singapore Department of Chemistry 3 Science Drive 3 Singapore117543 Singapore Advanced Membranes and Porous Materials Center Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Chemical Engineering Program Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia National University of Singapore Environmental Research Institute T Lab Building 5A Engineering Drive 1 Singapore117411 Singapore

In the present work, an aptasensor with dual binding sites based on Au NPs modified with self-polymerized polydopamine (PDA) and Fe-MOF is successfully constructed. In terms of standard electron transfer, the cyclic voltammetry (CV) analysis showcases a rate constant (ks) of 96.0 s-1, signifying an exceptional electron transfer rate of oxytetracycline at the sensor interface of Apt/Au@PDA@NH2-MIL-101(Fe)/GCE. Further deepening the investigation into electrochemical kinetics using chronoamperometry (CA), we investigated the electrocatalytic parameters (Kcat) of Au@PDA@NH2-MIL-101(Fe) in relation to oxytetracycline. The results divulged an impressive average Kcat value of 3.06×105 M-1 S-1. This evidence robustly suggests the superior electrocatalytic activity of Au@PDA@NH2-MIL-101(Fe) when it comes to oxytetracycline oxidation. A custom-designed portable rapid detection platform was developed, achieving detection limits of 6.88 nM under static water flow conditions and 5.56 nM under dynamic conditions. Remarkably, the self-polymerization of PDA on Au NPs not only refines their size but also boosts their interaction with biomolecules, thereby promising excellent biocompatibility. Moreover, the abundance of -COOH groups and unsaturated Fe3+ sites on the NH2-MIL-101(Fe) surface furnishes a considerable number of grafting sites for the aptamer. More importantly, the redox interplay between Au@PDA and NH2-MIL-101(Fe) accelerates electron movement, thus amplifying the electrochemical signal and the detection sensitivity for oxytetracycline. © 2024, The Authors. All rights reserved.

关键词： Rate constants

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Comparison between technical parameters recommended by regulatory agencies and relevant institutions for ventilatory therapy equipment used in patients with COVID-19

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Research on Biomedical engineering 2021年第2期37卷 375-388页

作者： de Souza, Daniel Baldoino Frondana, Fernanda Vieira Silva, Fábia Diniz Centre for Innovation and Technology Assessment in Health Postgraduate Program in Electrical and Biomedical Engineering Faculty of Electrical Engineering Federal University of Uberlândia Uberlândia Brazil Health Science Center Postgraduate Program in Health Management and Innovation Federal University of Rio Grande do Norte Natal Brazil Pneumology Division Heart Institute at Clinical Hospital Faculty of Medicine University of São Paulo São Paulo Brazil

Background: Patients contaminated with the new coronavirus, SARS-CoV-2, and who develop the severe form of the disease require ventilatory support to maintain adequate gas exchange. The objective of this systematic review was to establish reference parameters of ventilator therapy used in the various levels of severity of adult patients affected by COVID-19 to assist health professionals and hospital managers who will purchase this equipment. Methods: It used four databases: Medline, Cochrane Central, Scielo, and Pubmed. Restrictions applied as to the language, restricted to English, and to the patient’s profile, only adults affected by SARS-CoV-2. The review process was carried out by three independent reviewers using the PRISMA-P method. Results: Nineteen articles were included, in addition to the recommendations of the Brazilian Association of Intensive Care Medicine (Brazil), Federal Commission for Protection against Health Risks (Mexico), Medicines and Healthcare Products Regulatory Agency (UK), Pan American Health Organization, and World Health Organization. The types of ventilatory therapies found in the articles eligible for this study were continuous positive airway pressure (CPAP), non-invasive ventilation (NIV), and invasive mechanical ventilation (IMV). For each ventilatory therapy, the parameters presented in the article and the recommendations of regulatory agencies and relevant institutions were compared and analyzed. Conclusion: It was possible to suggest a relationship between the respiratory support strategy adopted by the clinical team and the clinical conditions of the patient infected with SARS-CoV-2. The included studies used ventilation modes and parameters within the specifications and recommendations of relevant regulatory agencies and institutions. However, some minor differences were observed in the instruction presented among the agencies more related to the recommended ventilation modes. Further studies are needed. © 2021, Sociedade Bras

关键词： Coronavirus

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Light-driven single-cell rotational adhesion frequency assay

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eLight 2022年第1期2卷 154-164页

作者： Yaoran Liu Hongru Ding Jingang Li Xin Lou Mingcheng Yang Yuebing Zheng Department of Electrical and Computer Engineering The University of Texas at AustinAustinTX 78712USA Walker Department of Mechanical Engineering The University of Texas at AustinAustinTX 78712USA Materials Science&Engineering Program and Texas Materials Institute The University of Texas at AustinAustinTX 78712USA School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China Beijing National Laboratory for Condensed Matter Physics and Laboratory of Soft Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China Songshan Lake Materials Laboratory Dongguan 523808GuangdongChina Department of Biomedical Engineering The University of Texas at AustinAustinTX 78712USA

The interaction between cell surface receptors and extracellular ligands is highly related to many physiological processes in living *** techniques have been developed to measure the ligand-receptor binding kinetics at the single-cell ***,few techniques can measure the physiologically relevant shear binding affinity over a single cell in the clinical ***,we develop a new optical technique,termed single-cell rotational adhesion frequency assay(scRAFA),that mimics in vivo cell adhesion to achieve label-free determination of both homogeneous and heterogeneous binding kinetics of targeted cells at the subcellular ***,the scRAFA is also applicable to analyze the binding affinities on a single cell in native human *** its superior performance and general applicability,scRAFA is expected to find applications in study of the spatial organization of cell surface receptors and diagnosis of infectious diseases.

关键词： diagnosis kinetics rotational

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Physics Constrained Multi-Objective Bayesian Optimization to Accelerate 3d Printing of Thermoplastics

SSRN

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SSRN 2024年

作者： Lin, Jian Sattari, Kianoosh Wu, Yuchao Chen, Zhenru Mahjoubnia, Alireza Su, Changhua Department of Mechanical and Aerospace Engineering University of Missouri ColumbiaMO65211 United States Department of Electrical Engineering and Computer Science University of Missouri ColumbiaMO65211 United States Food Science Program Division of Food Nutrition & Exercise Sciences University of Missouri ColumbiaMO65211 United States

Vat photopolymerization (VPP) of thermoplastics faces an issue of unpredictable printability due to the involved competing photopolymerization and dissolution reactions. The printing outcome largely depends on physicochemical properties of monomers and their compositions in resins, which also greatly determine the material properties, e.g., strength/toughness and phase transition temperature (Tg). Thus, a methodology for optimizing the resin formulation is of paramount importance in realizing highly printable thermoplastics with balanced strength/toughness and target Tg while remaining largely underexplored. Herein, we introduce a multi-objective Bayesian optimization (MOBO) algorithm with two physics informed constraints (printability and Tg) to optimize two conflicting properties: tensile strength (σT) and toughness (UT). The two constraints are formulated as two machine learning (ML) models, which are trained with weight ratios of the six input monomers and physics informed (PI) descriptors derived from their physiochemical parameters. Dimensional reduction analysis reveals that the algorithm avoids recommendation of the monomer ratios that do not pass the two constraints. The printing failure rate is reduced from 16% in the background experiments to 3% in the recommended experiments. Within only 36 iterations (72 samples), the MOBO algorithm successfully identifies five sets of ratios leading to Pareto optimal of σT and UT. Due to the constraint in Tg they show appropriate Tg for shape memory application. The partial dependence analysis indicates that σT and UT depend on both the ratios and physiochemical features of the monomers. These results underscore capability of such a smart decision-making algorithm—with constraints that are not fully understood but can be informed by prior knowledge—in planning the experiments from the vast design space, thus holding a great promise for broader applications in materials and manufacturing. © 2024, The Authors. All rights

关键词： Resins

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