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multi-kernel and multi-scale learning based deep ensemble model for predicting recurrence of non-small cell lung cancer

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PeerJ Computer Science 2023年 9卷

作者： Kim, Gihyeon Park, Young Mi Yoon, Hyun Jung Choi, Jang-Hwan Department of Computational Medicine Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Department of Molecular Medicine College of Medicine Ewha Womans University Seoul Korea Republic of Department of Radiology Veterans Health Service Medical Center Seoul Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Department of Artificial Intelligence Ewha Womans University Seoul Korea Republic of

Predicting recurrence in patients with non-small cell lung cancer (NSCLC) before treatment is vital for guiding personalized medicine. Deep learning techniques have revolutionized the application of cancer informatics, including lung cancer timeto-event prediction. Most existing convolutional neural network (CNN) models are based on a single two-dimensional (2D) computational tomography (CT) image or three-dimensional (3D) CT volume. However, studies have shown that using multiscale input and fusing multiple networks provide promising performance. This study proposes a deep learning-based ensemble network for recurrence prediction using a dataset of 530 patients with NSCLC. This network assembles 2DCNNmodels of various input slices, scales, and convolutional kernels, using a deep learning-based feature fusion model as an ensemble strategy. The proposed framework is uniquely designed to benefit from (i) multiple 2D in-plane slices to provide more information than a single central slice, (ii) multi-scale networks and multi-kernel networks to capture the local and peritumoral features, (iii) ensemble design to integrate features from various inputs and model architectures for final prediction. The ensemble of five 2D-CNN models, three slices, and two multi-kernel networks, using 5×5 and 6×6 convolutional kernels, achieved the best performance with an accuracy of 69.62%, area under the curve (AUC) of 72.5%, F1 score of 70.12%, and recall of 70.81%. Furthermore, the proposed method achieved competitive results compared with the 2D and 3D-CNN models for cancer outcome prediction in the benchmark studies. Our model is also a potential adjuvant treatment tool for identifying NSCLC patients with a high risk of recurrence. © 2023 Kim et al.

关键词： Neural network models

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Frailty and Other Factors Associated With Early Outcomes in Middle-to Older Age Trauma Patients: A Prospective Cohort Study

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American Journal of Geriatric Psychiatry 2024年第2期32卷 244-255页

作者： Yeh, Tian-Shin Kang, Jiunn-Horng Littlejohns, Thomas J. Wu, Chia-Chieh Chen, Jin-Hua Piravej, Krisna Chiu, Wen-Ta Lam, Carlos Department of Physical Medicine and Rehabilitation School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Department of Physical Medicine and Rehabilitation Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Epidemiology and Nutrition Harvard T. H. Chan School of Public Health Harvard University Boston MA United States Department of Physical Medicine and Rehabilitation National Taiwan University Hospital Taipei Taiwan Department of Physical Medicine and Rehabilitation College of Medicine National Taiwan University Taipei Taiwan Department of Physical Medicine and Rehabilitation Taipei Medical University Hospital Taipei Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei Taiwan International Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Nuffield Department of Population Health University of Oxford Oxford United Kingdom Emergency Department Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Emergency School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Graduate Institute of Data Science College of Management Taipei Medical University Taipei Taiwan Institutional Research Center Office of Data Science Taipei Medical University Taipei Taiwan Biostatistics Center Department of Medical Research Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Rehabilitation Medicine Faculty of Medicine Chulalongkorn University Bangkok Thailand Department of Chula Neuroscience Center King Chulalongkorn Memorial Hospital Bangkok Thailand Graduate Institute of Injury Prevention and Control College of Public Health Taipei Medical University Taipei Taiwan AHMC Health System Alhambra CA United States

Objectives: To prospectively investigate associations of frailty and other predictor variables with functional recovery and health outcomes in middle-aged and older patients with trauma. Design: Single-center prospective cohort study. Setting: Emergency department of Wan Fang Hospital in Taiwan. Participants: Trauma patients aged 45 and older. Measurements: Frailty was assessed with the Clinical Frailty Scale (CFS). Injury mechanisms, pre-existing diseases, and fracture locations were recorded at baseline. The primary outcome was functional recovery assessed using the Barthel Index (BI). Secondary outcomes were new care needs, unscheduled return visits, and falls 3 months postinjury. Results: A total of 588 participants were included in the final analysis. For every one-point increase in the CFS, the multivariable-adjusted odds ratio (OR, 95% confidence interval [CI]) of failure to retain the preinjury BI was 1.34 (1.16–1.55);associations were consistent across levels of age and injury severities. Significant joint associations of frailty and age with poor functional recovery were observed. CFS was also associated with new care needs (OR for every one-point increase, 1.36, 95% CI, 1.17–1.58), unscheduled return visits (OR 1.26, 95% CI, 1.04–1.51), and falls (OR 1.23, 95% CI, 1.01–1.51). Other variables associated with failure to retain preinjury BI included road traffic accident and presence of hip fracture. Conclusion: Frailty was significantly associated with poor functional and health outcomes regardless of injury severity in middle-aged and older patients with trauma. Injury mechanisms and fracture locations were also significant predictors of functional recovery postinjury. © 2023 American Association for Geriatric Psychiatry

关键词： Clinical Frailty Scale Frailty functional recovery injury middle-to older age

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Dynamic Hierarchical Skeleton-Based Network for Human Action Recognition in Video Content

SSRN

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SSRN 2024年

作者： Yang, Hualin Li, Xiying Chen, Calvin Yu-Chian Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China - Preferred Program Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong Provincial Key Laboratory of Intelligent Transportation System Sun Yat-sen University Guangzhou China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China

Human skeleton-based action recognition represents a pivotal field of study, capturing the intricate interplay between physical dynamics and intentional actions. Current research primarily focuses on extracting structural and temporal information from static skeleton-based graphs, but they grapple with a myriad of challenges. These include 1) an absence of hierarchical structure in encoding the skeleton-based graphs;2) A requirement for substantial prior knowledge to interpret the diverse spatial dynamics within singular action labels;3) An intricate task of representing the multifaceted temporal dynamics of individual actions. To counter this issue, we propose DHS-Net, an innovative dynamic hierarchical skeleton-based network in video content. The proposed DHS-Net incorporates the DHS Block as a central element, effectively facilitating information exchange through node concentration and diffusion across both structural and temporal dimensions. Through this architectural design, DHS-Net extracts hierarchical representations, enhancing the comprehensive understanding of spatio-temporal dynamics and marking a significant advancement in human action recognition. Our rigorous experimental evaluations further substantiate DHS-Net's supremacy, outperforming several state-of-the-art benchmarks in skeleton-based action recognition and achieving remarkable prediction accuracy. © 2024, The Authors. All rights reserved.

关键词： Dynamics

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Mrf-Former: A Multi-Scale Resolution Fusion Approach for Addressing Scale Discrepancies in Remote Sensing Image Change Detection

SSRN

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SSRN 2024年

作者： Yang, Hualin Ouyang, Jiarui Cheng, Junhao Zhang, Wen Li, Hui Li, Xiying Chen, Calvin Yu-Chian Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China - Preferred Program Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong Provincial Key Laboratory of Intelligent Transportation System Sun Yat-sen University Guangzhou China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China Institute of Artificial Intelligence Guangzhou University Guangzhou China

Dealing with resolution variations in dual-temporal remote sensing images is challenging due to differences in sensor capabilities, altitudes, footprints, resampling, and data fusion. Conventional methods for different-resolution change detection struggle to effectively address these challenges, primarily due to insufficient consideration of global and local feature interactions. In this paper, we propose a novel change detection model that leverages the power of multi-scale resolution fusion(MRF). By incorporating the MRF-Block, our approach extracts hierarchical multi-scale features from the input data, enabling effective capture of contextual information at various granularities. This facilitates improved handling of resolution disparities and promotes interactions between global and local features. Experimental evaluations conducted on diverse datasets, demonstrate the effectiveness of our proposed model in achieving accurate change detection in dual-temporal remote sensing imagery, even in scenarios characterized by varying resolutions. Code is available on-line at https://***/yanghl1914/MRF-Former. © 2024, The Authors. All rights reserved.

关键词： Remote sensing

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A Novel Method for the Fabrication of Antibacterial Stainless Steel with Uniform Silver Dispersions by Silver Nanoparticle/Polyethyleneimine Composites

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Materials 2023年第10期16卷 3719-3719页

作者： Chih, Yu-Kun You, Jhu-Lin Lin, Wei-Hsuan Chang, Yen-Hao Tseng, Chun-Chieh Ger, Ming-Der Graduate School of Defense Science Chung Cheng Institute of Technology National Defense University Taoyuan335 Taiwan Department of Chemical and Materials Engineering Chung Cheng Institute of Technology National Defense University Taoyuan335 Taiwan System Engineering and Technology Program National Chiao Tung University Hsinchu300 Taiwan Combination Medical Device Technology Division Medical Devices and Opto-Electronics Equipment Department Metal Industries Research & Development Centre Kaohsiung821 Taiwan

Only a few studies have so far focused on the addition of silver to SS316L alloys by conventional sintering methods. Unfortunately, the metallurgical process of silver-containing antimicrobial SS is greatly limited due to the extremely low solubility of silver in iron and its tendency to precipitate at the grain boundaries, resulting in an inhomogeneous distribution of the antimicrobial phase and loss of antimicrobial properties. In this work, we present a novel approach to fabricate antibacterial stainless steel 316L by functional polyethyleneimine-glutaraldehyde copolymer (PEI-co-GA/Ag catalyst) composites. PEI is a highly branched cationic polymer, which makes it exhibit very good adhesion on the surface of the substrate. Unlike the effect of the conventional silver mirror reaction, the introduction of functional polymers can effectively improve the adhesion and distribution of Ag particles on the surface of 316LSS. It can be seen from the SEM images that a large number of silver particles are retained and well dispersed in 316LSS after sintering. PEI-co-GA/Ag 316LSS exhibits excellent antimicrobial properties and does not release free silver ions to affect the surrounding environment. Furthermore, the probable mechanism for the influence of the functional composites on the enhancement of adhesion is also proposed. The formation of a large number of hydrogen bonds and van der Waals forces, as well as the negative zeta potential of the 316LSS surface, can effectively enable the formation of a tight attraction between the Cu layer and the surface of 316LSS. These results meet our expectations of designing passive antimicrobial properties on the contact surface of medical devices. © 2023 by the authors.

关键词： Silver nanoparticles

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Impact of Image Enhancement for Osteoporosis Detection Based on Deep Learning Algorithm

Impact of Image Enhancement for Osteoporosis Detection Based...

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Computer system, Information Technology, and Electrical engineering (COSITE), International Conference on

作者： Riza Dianil Iman Roslidar Roslidar Kahlil Muchtar Amalia Amalia Mohammad Syaryadhi Alfatirta Mufti Novi Maulina Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Graduate School of System Designs Tokyo Metropolitan University Tokyo Japan Doctorate Student of Doctoral Program in Medical Sciences Faculty of Medicine Universitas Syiah Kuala Banda Aceh Indonesia

Osteoporosis can be defined as a degenerative disease with reduced bone mass and changes in bone architecture that can lead to bone fragility and the risk of fractures. This abnormality can be indicated by the bone density which in visual can be determined using X-Ray images. However, X-Ray images are susceptible to noise, while in image analysis image contrast affects deep learning abilities. Hence, the CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm is used as a contrast enhancement technique in X-Ray images. This study aims to build a deep learning model using the CLAHE-enhanced image dataset with the ResNet-50 and ResNet-101 architectures. The model was built using two different datasets, namely the original image dataset and the CLAHE-enhanced image dataset. The result shows that the highest performance is given by the ResNet-101 model using the CLAHE-enhanced image dataset with an accuracy rate of 96%, precision of 95%, specificity of 95%, recall of 97% and an Fl-score of 96%, respectively. By using the CLAHE algorithm, the resulting image has high contrast and looks better at displaying features in the image so as to produce better model performance.

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Development of Simultaneous Quantitative Analytical Method for Three Active Components of Agastache Rugosa in Human Plasma Using Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry

SSRN

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SSRN 2023年

作者： Rinik, Urmi Rahman Kim, Ji Eon Lee, Eunok Kwon, Oran Jung, Byung Hwa Center for Advanced Biomolecular Recognition Korea Institute of Science and Technology Seoul02792 Korea Republic of Division of Bio-medical Science and Technology KIST School University of Science and Technology Daejeon34113 Korea Republic of Department of Nutritional Science and Food Management Graduate Program in System Health Science and Engineering Ewha Womans University Korea Republic of

Abstract: Agastache rugosa contains phenolic compounds and flavonoids, and has been extensively used as a traditional herbal medicine. The major components in Agastache rugosa are rosmarinic acid, tilianin, and acacetin, for which several analytical techniques have been reported. However, these substances have yet to be simultaneously quantified in human plasma. In this study, we aimed to simultaneously determine the three active components of Agastacherugosa in human plasma by developing a reliable quantitative analytical method using ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). Chromatographic separation of the plasma samples was achieved using an ACQUITY UPLC® BEH C18 column with a gradient mobile phase of water and acetonitrile containing 0.1% formic acid. Mass spectrometric detection was performed using a triple quadrupole tandem mass spectrometer in negative electrospray ionization (ESI−) and multiple reaction monitoring (MRM) modes. The developed quantitative method was validated for the three active components. All three analytes exhibited a linear response over the ranges of 0.5–50 ng/mL for rosmarinic acid, 0.1–20 ng/mL for acacetin, and 0.5–20 ng/mL for tilianin with a weighting factor of 1/x (where x is the concentration). At three quality control (QC) concentration levels (low, medium, and high), including the lower limit of quantitation (LLOQ), acceptable accuracy (±15%) was achieved in the intra- and interday validations. The concentration of rosmarinic acid was highest in plasma. Tilianin and acacetin appeared and were eliminated earlier in the plasma than rosmarinic acid. This study provides a successfully validated method that can be used in further clinical applications of Agastache rugosa extracts. © 2023, The Authors. All rights reserved.

关键词： Mass spectrometers

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Effect of Surface Activation on the Corrosion Resistance of a MAO/Ni-P Composite Coating on LZ91 Magnesium Alloy

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Journal of the Taiwan Institute of Chemical Engineers 2023年第1期147卷

作者： Chen, Chi-An Lee, Jeou-Long Jian, Shun-Yi Lee, Chia-Yu Ger, Ming-Der Combination Medical Device Technology Division Medical Devices R&D Service Department Metal Industries Research & Development Centre Kaohsiung802 Taiwan Department of Chemical and Materials Engineering Lung Hwa University of Science and Technology Taoyuan330 Taiwan Department of Material Engineering Ming Chi University of Technology New Taipei City Taiwan Center for Plasma and Thin Film Technologies Ming Chi University of Technology New Taipei Taiwan Graduate School of Defense Science Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan Department of Chemical & Materials Engineering Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan System Engineering and Technology Program National Chiao Tung University Hsin-Chu Taiwan

Background: LZ91 Magnesium alloy with a dual-phase structure has improved mechanical properties and a low density of about 1.48 g/cm3 but their limited resistance to corrosion limits their application. Therefore, it is a great challenge to increase the stability of LZ91 alloys under corrosive factors and environments. Methods: This study uses micro-arc oxidation (MAO) and an electroless nickel-phosphorus (Ni-P) plated composite film to increase the corrosion resistance of LZ91 magnesium alloy. Before electroless Ni-P plating, the MAO layers are activated by palladium catalysts at different pH values to produce composite coatings. SEM, EDS and Image J are used to determine the surface properties and elemental composition of the samples. The corrosion resistance is measured using a potentiodynamic polarization test and electrochemical impedance spectroscopy (EIS) in 3.5 wt.% NaCl solution. Findings: The results show that the MAO coating is activated by an acid catalyst and the surface is obviously corroded. The electroless Ni-P plating grows into the MAO coating and the substrate corrodes. Therefore, corrosive medium (chloride ion) easily enter to the substrate and pitting corrosion occurred. On the contrary, activation by a neutral catalyst (pH=7) maintains the original structure of the MAO coating and provides a good bonding interface for the Ni-P coating. Form the potentiodynamic analysis can be finds that the corrosion potential for the neutral catalyst treated sample is -0.35V and the corrosion current density value is 1.77×10−6 A/cm2, so the corrosion characteristic become better than the acid catalyst treated samples. In terms of the long-term resistance after 48 h, EIS analysis shows that the resistance value remains at about 7.6×104 Ω•cm2. A composite coating that is compact and with excellent resistance to corrosion resistance is produced, which provides better protection for LZ91 magnesium alloys. © 2023 Taiwan Institute of Chemical Engineers

关键词： Corrosion resistance

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Saca chip enabled circulating tumor cell clusters phenotyping for cancer immunotherapy response monitoring 24

Saca chip enabled circulating tumor cell clusters phenotypin...

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24th International Conference on Miniaturized systems for Chemistry and Life Sciences, MicroTAS 2020

作者： Hsu, Chun-Jieh Kan, Yu-Chia Lee, Chun-Wei Wu, Jen-Kuei Lee, Kang-Yun Feng, Po-Hao Chang, Wei-Chiao Tseng, Fan-Gang Department of Engineering and System Science National Tsing Hua University Taiwan Nano Science and Technology Program International Graduate Program Academia Sinica Taiwan Research Center for Applied Sciences Academia Sinica Taiwan Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University Taiwan Division of Pulmonary Medicine Department of Internal Medicine School of Medicine College of Medicine Taipei Taiwan School of Pharmacy Department of Clinical Pharmacy Taipei Medical University Taiwan

ISBN: (纸本)9781733419017

In the present study, we indicated that the detection of specific subtypes of circulating tumor microemboli (CTM) in post-operative patients could help predict cancer recurrence. By using conventional strategies for detection of non-small-cell lung cancer (NSCLC) circulating tumor cells, is significantly limited due to inherently heterogeneous and dynamic expression of EpCAM, and degradation of cytokeratins during epithelial-tomesenchymal transition. These lead to non-negligible false negative detection of "uncapturable and invisible" single CTCs. To solve the problem, we investigated the clinical significance of CTM subtypes, including single CTCs, multi-CTCs cluster, and WBC-CTCs cluster on SACA chip for studying cancer metastasis and recurrence in patients with lung adenocarcinoma. © 2020 CBMS-0001

关键词： Tumors

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