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Durable CRISPR-Based Epigenetic Silencing

BioDesign Research 2021年第1期2021卷 39-46页

作者： Muneaki Nakamura Alexis E.Ivec Yuchen Gao Lei S.Qi Department of Bioengineering StanfordCA 94305USA Program in Human Biology StanfordCA 94305USA Cancer Biology Program StanfordCA 94305USA Department of Chemical and Systems Biology StanfordCA 94305USA ChEM-H Institute StanfordCA 94305USA

Development of CRISPR-based epigenome editing tools is important for the study and engineering of biological ***,we describe the design of a reporter system for quantifying the ability of CRISPR epigenome editors to produce a stable gene *** characterize the dynamics of durable gene silencing and reactivation,as well as the induced epigenetic changes of this *** report the creation of single-protein CRISPR constructs bearing combinations of three epigenetic editing domains,termed KAL,that can stably repress the gene *** system should allow for the development of novel epigenome editing tools which will be useful in a wide array of biological research and engineering applications.

关键词： expression behavior CRISPR

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Temperature-sensitive polymeric nanogels encapsulating withβ-cyclodextrin and ICG complex for high-resolution deep-tissue ultrasound-switchable fluorescence imaging

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Nano Research 2020年第4期13卷 1100-1110页

作者： Ruilin Liu Tingfeng Yao Yang Liu Shuai Yu Liqin Ren Yi Hong Kytai T.Nguyen Baohong Yuan Ultrasound and Optical Imaging Laboratory Department of Bioengineeringthe University of Texas at ArlingtonArlingtonTX 76019USA Joint Biomedical Engineering Program the University of Texas at Arlington and the University of Texas Southwestern Medical CenterDallasTX 75390USA Department of Bioengineering the University of Texas at ArlingtonArlingtonTX 76019USA

One of the thorny problems currently impeding the applications of the fluorescence imaging technique is the poor spatial resolution in deep ***-switchable fluorescence(USF)imaging is a novel imaging tool that has recently been explored to possibly surmount the above-mentioned ***,αβ-cyclodextrin/indocyanine green(ICG)complex-encapsulated poly(N-isopropylacrylamide)(PNIPAM)nanogel was synthesized and studied for ex vivo/in vivo deep tissue/high-resolution near infrared USF(NIR-USF)*** be specific,our results revealed that the average diameter of the as-prepared nanogels was significantly decreased to-32 nm from-335 nm compared to the reported ICG-PNIPAM ***,the excitation/emission characteristics of the ICG itself in present nanogels were almost completely retained,and the resultant nanogel exhibited high physiological stability and positive *** particular,the signal-to-noise ratio of the USF image for the PNIPAM/P-cyclodextrin/ICG nanogel(33.01±2.42 dB)was prominently higher than that of the ICG-PNIPAM nanoparticles(18.73±0.33 dB)in 1.5-cm-thick chicken breast *** NIR-USF imaging in 3.5-cm-thick chicken breast tissues was achieved using this new *** e x v iv o NIR-USF imaging of the mouse liver was also successfully *** experiments showed that the present nanogels were able to be effectively accumulated into U87 tumor-bearing mice via enhanced permeability and retention effects,and the high-resolution NIR-USF imaging of in v ivo tumor was efficiently *** metabolism and in vivo biodistribution of the nanogels were ***,the results suggest that the current nanogel is a highly promising NIR-USF probe for deep tissue and high-resolution USF imaging.

关键词： deep tissue imaging high-resolution ultrasound-switchable NIR fluorescence imaging in vivo imaging

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Quality analysis and study of tuberculosis diagnostic data

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Procedia Computer Science 2024年 239卷 939-946页

作者： Ana Clara de Andrade Mioto Pedro Emilio Andrade Martins Gabriel Modina Domingos Alves Vinicius Costa Lima Mariane Neiva Filipe Andrade Bernardi Bioengineering Postgraduate Program University of São Paulo São Carlos Brazil Ribeirão Preto Medical School University of São Paulo Ribeirão Preto Brazil Institute of Mathematical and Computer Sciences University of São Paulo Ribeirão Preto Brazil

According to the World Health Organization (WHO), annually, 10 million people suffer from Tuberculosis (TB) worldwide, an infection caused by the bacteria Mycobacterium tuberculosis. Clinical data is complex and characterized by heterogeneity, making the interoperability of systems challenging and impairing the availability, integration, and quality of data, essential for health activity. This negatively impacts both patient treatment and decision-making. At the data level, the identification and evaluation of the best quality attributes of clinical data and recommendations available in different articles explored during the article, will be carried out. The analysis will also look for data clusters that do not meet these recommendations, in order to identify unknown patterns that may help to understand the mechanisms behind the data quality and, consequently, the expected results for the evaluated project.

关键词： Tuberculosis Quality Analysis FAIR

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OVERVIEW OF PROCESSING TECHNIQUES FOR SURFACE ELECTROMYOGRAPHY SIGNALS

arXiv

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arXiv 2023年

作者： Manjarres-Triana, Alejandra Acevedo-Serna, Juan Ramírez-Duque, Andrés A. Jiménez, Mario F. Pulido-Herrera, Edith Villarejo Mayor, John J. Bioengineering Program Universidad El Bosque Bogotá Colombia School of Computing Science University of Glasgow Glasgow United Kingdom School of Engineering Science and Technology Universidad del Rosario Bogotá Colombia Postgraduation Program of Physical Education Federal University of Parana Curitiba Brazil

Surface electromyography (sEMG) is a technology to assess muscle activation, which is an important component in applications related to diagnosis, treatment, progression assessment, and rehabilitation of specific individuals’ conditions. Recently, sEMG potential has been shown, since it can be used in a non-invasive manner;nevertheless, it requires careful signal analysis to support health professionals reliably. This paper briefly described the basic concepts involved in the sEMG, such as the physiology of the muscles, the data acquisition, the signal processing techniques, and classification methods that may be used to identify disorders or signs of abnormalities according to muscular patterns. Specifically, classification methods encompass digital signal processing techniques and machine learning with high potential in the field. We hope that this work serves as an introduction to researchers interested in this *** Codes 92C55 (Primary), 94A99 (secondary) © 2023, CC BY.

关键词： Machine learning

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EDM: Enhancing Quality Diversity of Medical Image Augmentation Under the User-specified Complex and Various Conditions

EDM: Enhancing Quality Diversity of Medical Image Augmentati...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S. Y. Kim H. B. Chung J. S. Lee M. J. Kang Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Republic of Korea Seoul National University Nuclear Medicine Bioengineering and Biomedical Sciences Seoul Republic of Korea Seoul National University Mathematical Sciences Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In the medical domain, the scarcity of data leads to class imbalances and fairness issues, significantly impairing deep learning performance and leading to the underrepresentation of minority patient groups. To address these challenges, data augmentation techniques employing Generative Adversarial Networks (GANs) and diffusion models have been extensively explored, with diffusion models particularly noted for their ability to enhance data diversity and quality. Despite their achievements, it remains a challenging task to generate a diverse range of samples from limited datasets and to achieve precise generation of images that align with user *** overcome these limitations, we propose a framework, EDM (Enhancing Quality Diversity of Medical image augmentation under the user-specified complex and various conditions), designed to generate diverse high-quality medical images under the various and complex multimodal conditions, representing age, sex, and diseases. Our framework comprises four steps. First, we propose a metric to quantize the necessity of data augmentation. Second, we prepare data augmentation. We generate medical sketch-image-text triplets using DiffSketcher from the real patients’ dataset. Then we employ these triplets to train ControlNet, enabling the generation of synthetic medical images from sketch data. Third, we generate synthetic medical images. We obtain multiple sketches for each image from a diversity-enhanced DiffSketcher, incorporating similarity loss. Using these sketches, we augment data from the fine-tuned ControlNet from the second step. Lastly, we introduce a metric to measure the diversity of the generated images, ensuring the effectiveness of our augmentation *** preliminary experimental results imply EDM can be the promising solution. Future experiments are planned to construct synthetic datasets of various modalities such as PET and CT for underrepresented patient groups.

关键词： Semiconductor device measurement Microwave integrated circuits Semiconductor detectors Data augmentation Diffusion models Generative adversarial networks Image augmentation

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Accelerated Direct PET Attenuation and Scatter Corrections Using Generation-Prior Diffusion Model (GPDM)

Accelerated Direct PET Attenuation and Scatter Corrections U...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： M.J. Cho H.S. Shim J.S. Lee Interdisciplinary Program of Bioengineering Seoul National University Seoul Republic of Korea Integrated Major in Innovative Medical Science Seoul National University Seoul Republic of Korea Department of Nuclear Medicine Seoul National University Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

Attenuation and scatter corrections play pivotal roles in PET image processing for accurate quantification. While CT-based corrections are conventional, they encounter limitations such as respiratory motion and metal artifacts. Recent advances in generative deep neural networks offer promising alternatives by directly estimating attenuation and scatter-corrected (ASC) PET from non-attenuation and non-scatter-corrected (NASC) PET. In GAN-based methods, the generator typically learns to map input data to the desired output (e.g. NASC PET to ASC PET) in one step. While this approach can be effective in generating realistic images, it often encounters significant challenges, such as unstable training and mode collapse. On the other hand, Denosing Diffusion Probabilistic Model (DDPM), a recent innovative solution based on probability theory, has emerged to address these issues, and gradually refines the image over numerous steps (e.g., 1,000 steps). In our previous study, a conditional DDPM (cDDPM) model, where the diffusion process was conditioned with NASC PET to generate ASC PET, outperformed conventional CycleGAN and conditional GAN (cGAN) approaches in the direct PET attenuation and scatter corrections [1]. However, the high computational complexity is one of the main drawbacks of DDPM. The training and inference steps of DDPM can be computationally intensive, requiring significant resources in terms of time, memory, and hardware. To overcome these problems, this study proposes a new acceleration method for the fast learning and sampling process of DDPM. In this method, named Generation-Prior Diffusion Model (GPDM), cDDPM is conditioned with prior variables obtained by applying a U-NET or cGAN to generate ASC PET from NASC PET. GPDM can significantly reduce the sampling steps owing to the high similarity between conditioned images and ASC PET. Consequently, computational complexity can be effectively decreased.

关键词： Training Microwave integrated circuits Semiconductor detectors Image processing Memory management Metals Attenuation

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An information system for monitoring tuberculosis cases: Implementation research protocol using RE-AIM for a health region in Brazil

An information system for monitoring tuberculosis cases: Imp...

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2022 International Conference on ENTERprise Information Systems, CENTERIS 2022 - International Conference on Project MANagement, ProjMAN 2022 and International Conference on Health and Social Care Information Systems and Technologies, HCist 2022

作者： Crepaldi, Nathalia Yukie Lima, Vinicius Costa Bernardi, Filipe Andrade Alves, Domingos Ribeirão Preto Medical School University of São Paulo Ribeirão Preto14049-900 Brazil Bioengineering Postgraduate Program University of São Paulo São Carlos13566-590 Brazil Department of Social Medicine Ribeirão Preto Medical School University of São Paulo Ribeirão Preto14049-900 Brazil

Tuberculosis is an infectious bacterial disease and one of the biggest public health problems in the world despite being curable. Research is still needed that considers operational aspects of treatment and control of its spread. Considering this scenario, the need to develop software that provides real-Time information about the patient's path along health information systems for clinical decision-making is fundamental. Because of this, a region made up of 26 municipalities will implement a computerized system to monitor tuberculosis cases, the SISTB. However, the implementation of new technology can result in the creation of new functions and cause changes in the existing ones. Implementation research can be used as an approach where evidence can be provided to guide the use of digital technology in tuberculosis care. The RE-AIM framework provides a model to inform this research. Thus, this work aims to report the protocol of a study to evaluate the implementation of a health information system to assist in the monitoring of tuberculosis treatment, using the RE-AIM. The implementation will be carried out in 5 phases: i) define the locations that will receive the intervention;ii) prepare people to receive the intervention iii) train key people;iv) adapt the SISTB and/or the training according to the discussions in the previous phase;v) follow up and monitor the support of the technology. The data collected for the evaluation will come from the database of the implemented system, questionnaires, and training meetings. The forecast for the study conclusion is the end of 2023. As a result, we hope that the SISTB implementation will increase the positive outcomes of tuberculosis patients' treatment. © 2023 Elsevier B.V.. All rights reserved.

关键词： Patient treatment

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Deformable Image Registration Using Vision Transformers for Cardiac Motion Estimation from Cine Cardiac MRI Images 12th

Deformable Image Registration Using Vision Transformers for...

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Functional Imaging and Modeling of the Heart - 12th International Conference, FIMH 2023, Proceedings

作者： Upendra, Roshan Reddy Simon, Richard Shontz, Suzanne M. Linte, Cristian A. Center for Imaging Science Rochester Institute of Technology RochesterNY United States Biomedical Engineering Rochester Institute of Technology RochesterNY United States Electrical Engineering and Computer Science University of Kansas LawrenceKS United States Bioengineering Program University of Kansas LawrenceKS United States Institute for Information Sciences University of Kansas LawrenceKS United States

ISBN: (纸本)9783031353017

Accurate cardiac motion estimation is a crucial step in assessing the kinematic and contractile properties of the cardiac chambers, thereby directly quantifying the regional cardiac function, which plays an important role in understanding myocardial diseases and planning their treatment. Since the cine cardiac magnetic resonance imaging (MRI) provides dynamic, high-resolution 3D images of the heart that depict cardiac motion throughout the cardiac cycle, cardiac motion can be estimated by finding the optical flow representation between the consecutive 3D volumes from a 4D cine cardiac MRI dataset, thereby formulating it as an image registration problem. Therefore, we propose a hybrid convolutional neural network (CNN) and Vision Transformer (ViT) architecture for deformable image registration of 3D cine cardiac MRI images for consistent cardiac motion estimation. We compare the image registration results of our proposed method with those of the VoxelMorph CNN model and conventional B-spline free form deformation (FFD) non-rigid image registration algorithm. We conduct all our experiments on the open-source Automated Cardiac Diagnosis Challenge (ACDC) dataset. Our experiments show that the deformable image registration results obtained using the proposed method outperform the CNN model and the traditional FFD image registration method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image registration

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Resistive-pulse sensing tumor-derived exosome detection device for resrouce-limited settings 21

Resistive-pulse sensing tumor-derived exosome detection devi...

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21st International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2017

作者： Carey, Thomas R. Yu, Connie W. Sohn, Lydia L. UC Berkeley-UCSF Graduate Program in Bioengineering United States UC Berkeley Bioengineering United States UC Berkeley Mechanical Engineering United States

ISBN: (纸本)9780692941836

We present the theory, design, and initial characterization of a tumor-derived exosome detection platform based on resistive-pulse sensing to enable cost-effective, point-of-care cancer screening. Our platform detects exosomes displaying a specific surface antigen by electronically measuring the effective size increase that occurs when exosomes bind to colloids functionalized with a specific antibody. We have demonstrated that our device can distinguish antibody-functionalized colloids from similar colloids incubated with SKBR3-derived exosomes. © 17CBMS-0001.

关键词： Colloids

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Glycerol Electrooxidation over Precision-Synthesized Gold Nanocrystals with Different Surface Facets

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Precision Chemistry 2024年第3期2卷 103-111页

作者： Hansen Mou Fang Lu Zechao Zhuang Qiaowan Chang Lihua Zhang Xiaobo Chen Yugang Zhang Jingguang G.Chen Department of Chemical Engineering Columbia UniversityNew YorkNew York 10027United States School of Chemical Engineering and Bioengineering Washington State UniversityPullmanWashington 99164United States Center for Functional Nanomaterials Brookhaven National LaboratoryUptonNew York 11973United States Materials Science and Engineering Program State University of New York at BinghamtonBinghamtonNew York 13902United States Chemistry Division Brookhaven National LaboratoryUptonNew York 11973United States

Electrochemical glycerol oxidation(EGO)emerges as a promising route to valorize glycerol,an underutilized byproduct from biodiesel production,into value-added *** study employed three types of gold(Au)nanocrystals with controlled shapes to elucidate the facet-dependent electrocatalytic behavior in ***,rhombic dodecahedral,and cubic Au nanocrystals with{111},{110},and{100}facets,respectively,were precisely synthesized with uniform size and *** dodecahedra exhibited the lowest onset potential for EGO due to facile AuOH formation,while octahedra showed enhanced electrochemical activity for glycerol oxidation and resistance to ***-situ FTIR analysis revealed that Au{111}surfaces selectively favored C_(2) products,whereas Au{100}surfaces promoted C_(3) product formation,highlighting the significant effect of facet orientation on EGO performance and informing catalyst design.

关键词： Electrochemical glycerol oxidation Precision synthesis Shaped nanocrystals Au nanocrystals SAXS In-situ FTIR

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