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Toward a blood-brain barrier microphysiological system with in-line monitoring 23

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Toward a blood-brain barrier microphysiological system with ...

23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019

作者： Young, Ashlyn T. Pozdin, Vladimir A. Daniele, Michael Joint Department of Biomedical Engineering NC State and UNC Chapel HillNC United States Department of Electrical and Computer Engineering NC State NC United States

ISBN: (纸本)9781733419000

Microphysiological systems (MPS) incorporate physiologically relevant microanatomy, mechanics, and cells to mimic tissue function. MPS can be used for drug screening, developmental biology, pathology, and toxicology research. Uniquely enabled by in situ formation of 3D tissue, we engineered a MPS of the BBB (MPS-BBB) without a semi-permeable membrane, therefore simplifying assembly, enabling high-resolution imaging, and promoting astrocyte-endothelial interactions. Consequently, this system better recapitulates in vivo cellular pathways and functions. Characterization beyond post facto techniques is enabled through impedance monitoring of barrier fidelity with an in-line electrode array. In-line monitoring provides for real-time analyses to infer barrier development, dysfunction, and repair. © 2019 CBMS-0001.

关键词： Tissue

Autofocusing Technologies for Whole Slide Imaging and Automated Microscopy

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arXiv 2020年

作者： Bian, Zichao Guo, Chengfei Jiang, Shaowei Zhu, Jiakai Wang, Ruihai Song, Pengming Hoshino, Kazunori Zheng, Guoan University of Connecticut Department of Biomedical Engineering StorrsCT06269 United States University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States

Whole slide imaging (WSI) has moved digital pathology closer to diagnostic practice in recent years. Due to the inherent tissue topography variability, accurate autofocusing remains a critical challenge for WSI and automated microscopy systems. Traditional focus map surveying method is limited in its ability to acquire a high degree of focus points while still maintaining high throughput. Real-time approaches decouple image acquisition from focusing, thus allowing for rapid scanning while maintaining continuous accurate focus. This work reviews the traditional focus map approach and discuss the choice of focus measure for focal plane determination. It will also discuss various real-time autofocusing approaches including reflective-based triangulation, confocal pinhole detection, low-coherence interferometry, tilted sensor approach, independent dual sensor scanning, beam splitter array, phase detection, dual-LED illumination, and deep-learning approaches. The technical concepts, merits, and limitations of these methods are explained and compared to that of a traditional WSI system. This review may provide new insights for the development of high-throughput automated microscopy imaging systems that can be made broadly available and utilizable without loss of capacity. Copyright © 2020, The Authors. All rights reserved.

关键词： Automation

Fluorescence-enhanced mid-infrared photothermal microscopy

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arXiv 2021年

作者： Zhang, Yi Zong, Haonan Zong, Cheng Tan, Yuying Zhang, Meng Zhan, Yuewei Cheng, Ji-Xin Department of Physics Boston University BostonMA02215 United States Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Photonics Center Boston University BostonMA02215 United States

Mid-infrared photothermal microscopy is a new chemical imaging technology in which a visible beam senses the photothermal effect induced by a pulsed infrared laser. This technology provides infrared spectroscopic information at sub-micron spatial resolution and enables infrared spectroscopy and imaging of living cells and organisms. Yet, current mid-infrared photothermal imaging sensitivity suffers from a weak dependance of scattering on temperature and the image quality is vulnerable to the speckles caused by scattering. Here, we present a novel version of mid-infrared photothermal microscopy in which thermo-sensitive fluorescent probes are harnessed to sense the mid-infrared photothermal effect. The fluorescence intensity can be modulated at the level of 1% per Kelvin, which is 100 times larger than the modulation of scattering intensity. In addition, fluorescence emission is free of speckles, thus much improving the image quality. Moreover, fluorophores can target specific organelles or biomolecules, thus augmenting the specificity of photothermal imaging. Spectral fidelity is confirmed through fingerprinting a single bacterium. Finally, the photobleaching issue is successfully addressed through the development of a wide-field fluorescence-enhanced mid-infrared photothermal microscope which allows video rate bond-selective imaging of biological specimens. © 2021, CC BY-NC-ND.

关键词： Infrared devices

Multi-Frequency Reverberant Shear Waves for Assessing Tissue Dispersion in Optical Coherence Elastography

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arXiv 2025年

作者： Asemani, Hamidreza Meemon, Panomsak Barrera, Gilmer Flores Rolland, Jannick P. Parker, Kevin J. Institute of Optics University of Rochester RochesterNY14627 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States School of Physics Institute of Science Suranaree University of Technology Nakhon Ratchasima30000 Thailand Department of Biomedical Engineering University of Rochester RochesterNY14627 United States

Optical coherence elastography (OCE) is a powerful non-invasive imaging technique for high-resolution assessment of tissue elasticity and viscoelasticity. Accurate characterization of viscoelastic properties requires estimating shear wave speed (SWS) across multiple frequencies, as dispersion induces frequency-dependent variations in wave speed. This study introduces a novel multi-frequency reverberant OCE (MFR-OCE) approach to enhance viscoelastic tissue characterization by simultaneously capturing shear wave dynamics over multiple frequencies. We present the theoretical framework, experimental setup, and validation of MFR-OCE through simulations and experiments on gelatin phantoms, ex vivo porcine cornea, and ex vivo bovine liver. Simulation results demonstrate that MFR-OCE estimates SWS with errors below 4% relative to ground truth, and phantom experimental results show that MFR-OCE and single-frequency OCE also yield closely matching SWS estimates, with differences below 3%. Furthermore, the frequency-dependent dispersion coefficients extracted from biological tissues and phantoms align with the theoretical viscoelastic power law model. The gelatin phantoms exhibit a low viscoelastic behavior with an exponent of 0.13 for the power law fit of SWS, while the ex vivo porcine cornea demonstrates intermediate viscoelastic behavior, with a power law exponent of 0.33. The liver tissue shows significant frequency dependence, with a power law exponent of 0.51. These findings demonstrate that MFR-OCE enables a more comprehensive understanding of tissue mechanics and holds the potential for improving diagnostic accuracy in clinical applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Dispersion (waves)

High-Density Embedded Electronics in Textiles with 3D Flex Package Transfer

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High-Density Embedded Electronics in Textiles with 3D Flex P...

Electronic Components and Technology Conference (ECTC)

作者： Md Monirojjaman Monshi Jose-Solis Camara Shubhendu Bhardwaj John L. Volakis P. M. Raj Dept. of Biomedical Engineering Florida International University Miami FL USA Dept. of Electrical and Computer Engineering Florida International University Miami FL USA

ISBN: (数字)9781728161808

ISBN: (纸本)9781728161815

Hybrid device-flex-textile interconnect and integration technologies were developed to realize smart wireless sensing systems. Test vehicles were fabricated to emulate high-density 3D flex packages in textiles. Representative test chips were assembled onto patterned copper traces on Liquid Crystal Polymer (LCP) flex substrates. These flex circuits were embedded into textiles with deformable silver adhesive interconnects. Fluoroelastomers were utilized as encapsulants to suppress moisture permeation and interaction with the embedded electronics. Contact resistances of the flex-to-textile and device-to-flex interconnects were investigated after fabrication, flexing, thermal and humidity treatments. DC resistances were extracted through Kelvin Probe structures and their stability during thermal and humidity exposure conditions were investigated. In addition to DC resistance, RF loss performance was also improved when we use silver adhesive interconnects to replace bulky and inflexible solder interconnects.

关键词： Integrated circuit interconnections Textiles Flexible printed circuits Copper Silver Kelvin Probes

Unified Analysis on L1 over L2 Minimization for signal recovery

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arXiv 2021年

作者： Tao, Min Zhang, Xiao-Ping Department of Mathematics National Key Laboratory for Novel Software Technology Nanjing University Nanjing210093 China Department of Electrical Computer and Biomedical Engineering Ryerson University TorontoONM5B 2K3 Canada

In this paper, we carry out a unified study for L1 over L2 sparsity promoting models, which are widely used in the regime of coherent dictionaries for recovering sparse nonnegative/arbitrary signals. First, we provide a unified theoretical analysis on the existence of the global solutions of the constrained and the unconstrained L1/L2 models. Second, we analyze the sparse property of any local minimizer of these L1/L2 models which serves as a certificate to rule out the nonlocal-minimizer stationary solutions. Third, we derive an analytical solution for the proximal operator of the L1/L2 with nonnegative constraint. Equipped with this, we apply the alternating direction method of multipliers to the unconstrained model with nonnegative constraint in a particular splitting way, referred to as ADMM+p. We establish its global convergence to a d-stationary solution (sharpest stationary) without the Kurdyka-Lojasiewicz assumption. Extensive numerical simulations confirm the superior of ADMM+p over the state-of-the-art methods in sparse recovery. In particular, ADMM+p reduces computational time by about 95% ∼ 99% while achieving a much higher accuracy than the commonly used scaled gradient projection method for the wavelength misalignment *** Codes 90C26, 90C90 © 2021, CC BY.

关键词： Recovery

Unified Analysis on L1 over L2 Minimization for signal recovery

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TechRxiv

TechRxiv 2021年

In this paper, we carry out a unified study for L1 over L2 sparsity promoting models, which are widely used in the regime of coherent dictionaries for recovering sparse nonnegative/arbitrary signals. First, we provide a unified theoretical analysis on the existence of the global solutions of the constrained and the unconstrained L1/L2 models. Second, we analyze the sparse property of any local minimizer of these L1/L2 models which serves as a certificate to rule out the nonlocal-minimizer stationary solutions. Third, we derive an analytical solution for the proximal operator of the L1/L2 with nonnegative constraint. Equipped with this, we apply the alternating direction method of multipliers to the unconstrained model with nonnegative constraint in a particular splitting way, referred to as ADMM+p . We establish its global convergence to a d-stationary solution (sharpest stationary) without the Kurdyka-Lojasiewicz assumption. Extensive numerical simulations confirm the superior of ADMM+p over the state-of-the-art methods in sparse recovery. In particular, ADMM+p reduces computational time by about 95% ∼ 99% while achieving a much higher accuracy than the commonly used scaled gradient projection method for the wavelength misalignment problem. © 2021, CC BY.

关键词： Recovery

Angle-restricted fluorescent optical projection tomography to localize micromets in lymph nodes

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Angle-restricted fluorescent optical projection tomography t...

Bio-Optics: Design and Application, BODA 2019

作者： Torres, Veronica C. Li, Chengyue Sinha, Lagnojita Brankov, Jovan G. Tichauer, Kenneth M. Biomedical Engineering Illinois Institute of Technology ChicagoIL60616 United States Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

Angle-constrained optical projection tomography and filtered backprojection reconstruction are sufficient to detect and localize the smallest clinically relevant metastases in excised porcine lymph nodes. © 2019 ... 详细信息

ISBN: (纸本)9781943580545

关键词： Tomography

Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network

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PLoS Computational Biology 2021年第9期17卷 e1009345-e1009345页

作者： Zhao, Zhengqiao Woloszynek, Stephen Agbavor, Felix Mell, Joshua Chang Sokhansanj, Bahrad A. Rosen, Gail L. Ecological and Evolutionary Signal-Processing and Informatics Laboratory Department of Electrical and Computer Engineering College of Engineering Drexel University PhiladelphiaPA United States Beth Israel Deaconess Medical Center BostonMA United States Harvard Medical School BostonMA United States School of Biomedical Engineering Science and Health Systems Drexel University PhiladelphiaPA United States College of Medicine Drexel University PhiladelphiaPA United States

Recurrent neural networks with memory and attention mechanisms are widely used in natural language processing because they can capture short and long term sequential information for diverse tasks. We propose an integrated deep learning model for microbial DNA sequence data, which exploits convolutional neural networks, recurrent neural networks, and attention mechanisms to predict taxonomic classifications and sample-associated attributes, such as the relationship between the microbiome and host phenotype, on the read/ sequence level. In this paper, we develop this novel deep learning approach and evaluate its application to amplicon sequences. We apply our approach to short DNA reads and full sequences of 16S ribosomal RNA (rRNA) marker genes, which identify the heterogeneity of a microbial community sample. We demonstrate that our implementation of a novel attention- based deep network architecture, Read2Pheno, achieves read-level phenotypic prediction. Training Read2Pheno models will encode sequences (reads) into dense, meaningful representations: learned embedded vectors output from the intermediate layer of the network model, which can provide biological insight when visualized. The attention layer of Read2Pheno models can also automatically identify nucleotide regions in reads/sequences which are particularly informative for classification. As such, this novel approach can avoid pre/post-processing and manual interpretation required with conventional approaches to microbiome sequence classification. We further show, as proof-of-concept, that aggregating read-level information can robustly predict microbial community properties, host phenotype, and taxonomic classification, with performance at least comparable to conventional approaches. An implementation of the attention-based deep learning network is available at https://***/EESI/sequence_attention (a python package) and https://***/ EESI/seq2att (a command line tool). Copyright: © 2021 Zhao et

关键词： Classification (of information)