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arXiv 2022年

作者： Barrett, Aaron Brown, Jordan A. Smith, Margaret Anne Woodward, Andrew Vavalle, John P. Kheradvar, Arash Griffith, Boyce E. Fogelson, Aaron L. Department of Mathematics University of Utah Salt Lake CityUT United States Department of Mathematics University of North Carolina Chapel HillNC United States Advanced Medical Imaging Lab University of North Carolina Medical Center Chapel HillNC United States University of North Carolina School of Medicine Chapel HillNC United States Division of Cardiology Department of Medicine University of North Carolina Chapel HillNC United States Department of Biomedical Engineering University of California Irvine IrvineCA United States Department of Mathematics Applied Physical Sciences and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel HillNC United States McAllister Heart Institute University of North Carolina Chapel HillNC United States Department of Mathematics and Biomedical Engineering University of Utah Salt Lake CityUT United States

Subclinical leaflet thrombosis (SLT) is a potentially serious complication of aortic valve replacement with a bioprosthetic valve in which blood clots form on the replacement valve. SLT is associated with increased risk of transient ischemic attacks and strokes and can progress to clinical leaflet thrombosis. SLT following aortic valve replacement also may be related to subsequent structural valve deterioration, which can impair the durability of the valve replacement. Because of the difficulty in clinical imaging of SLT, models are needed to determine the mechanisms of SLT and could eventually predict which patients will develop SLT. To this end, we develop methods to simulate leaflet thrombosis that combine fluid-structure interaction and a simplified thrombosis model that allows for deposition along the moving leaflets. Additionally, this model can be adapted to model deposition or absorption along other moving boundaries. We present convergence results and quantify the model's ability to realize changes in valve opening and pressures. These new approaches are an important advancement in our tools for modeling thrombosis in which they incorporate both adhesion to the surface of the moving leaflets and feedback to the fluid-structure interaction. © 2022, CC BY-SA.

关键词： Deposition

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Composite B-Spline Regularized Delta Functions for the Immersed Boundary Method: Divergence-Free Interpolation and Gradient-Preserving Force Spreading

arXiv

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arXiv 2024年

作者： Gruninger, Cole Griffith, Boyce E. Department of Mathematics University North Carolina Chapel HillNC United States Department of Applied Physical Sciences University of North Carolina Chapel HillNC United States Department of Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina School of Medicine Chapel HillNC United States McAllister Heart Institute University of North Carolina School of Medicine Chapel HillNC United States

This paper presents an approach to enhance volume conservation in the immersed boundary (IB) method by employing regularized delta functions derived from composite B-splines. These delta functions are constructed using tensor product kernels, similar to the conventional IB method. However, the kernels are B-splines whose polynomial degree varies according to the normal and tangential directions of each velocity component. The conventional IB method, while effective for fluid-structure interaction applications, has long been challenged by poor volume conservation, particularly evident in simulations of pressurized, closed membranes. We demonstrate that composite B-spline regularized delta functions significantly enhance volume conservation through two complementary properties: they provide continuously divergence-free velocity interpolants and maintain the gradient character of forces corresponding to mean pressure jumps across interfaces. By correctly representing these forces as discrete gradients, they eliminate a key source of spurious flows that typically plague immersed boundary computations. Our approach maintains the local nature of the classical IB method, avoiding the computational overhead associated with the non-local Divergence-Free Immersed Boundary (DFIB) method’s construction of an explicit velocity potential which requires additional Poisson solves for interpolation and force spreading operations. Through a series of numerical experiments, we show that sufficiently regular composite B-spline kernels can maintain initial volumes to within machine precision. We provide a detailed analysis of the relationship between kernel regularity and the accuracy of force spreading and velocity interpolation operations. Our findings indicate that composite B-splines of at least C1 regularity produce results comparable to the DFIB method in dynamic simulations, with errors in volume conservation primarily dominated by truncation error of the employed time-stepping s

关键词： Delta functions

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Statistical Power Analysis for Designing Bulk, Single-Cell, and Spatial Transcriptomics Experiments: Review, Tutorial, and Perspectives

arXiv

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arXiv 2023年

作者： Jeon, Hyeongseon Xie, Juan Jeon, Yeseul Jung, Kyeong Joo Gupta, Arkobrato Chang, Won Chung, Dongjun Department of Biomedical Informatics The Ohio State University ColumbusOH United States Pelotonia Institute for Immuno-Oncology The James Comprehensive Cancer Center The Ohio State University ColumbusOH43210 United States The Interdisciplinary PhD program in Biostatistics The Ohio State University ColumbusOH United States Department of Statistics and Data Science Yonsei University Seoul Korea Republic of Department of Applied Statistics Yonsei University Seoul Korea Republic of Department of Computer Science and Engineering The Ohio State University ColumbusOH United States Division of Statistics and Data Science University of Cincinnati CincinnatiOH United States

Gene expression profiling technologies have been used in various applications such as cancer biology. The development of gene expression profiling has expanded the scope of target discovery in transcriptomic studies, and each technology produces data with distinct characteristics. In order to guarantee biologically meaningful findings using transcriptomic experiments, it is important to consider various experimental factors in a systematic way through statistical power analysis. In this paper, we review and discuss the power analysis for three types of gene expression profiling technologies from a practical standpoint, including bulk RNA-seq, single-cell RNA-seq, and high-throughput spatial transcriptomics. Specifically, we describe the existing power analysis tools for each research objective for each of the bulk RNA-seq and scRNA-seq experiments, along with recommendations. On the other hand, since there are no power analysis tools for high-throughput spatial transcriptomics at this point, we instead investigate the factors that can influence power analysis. © 2023, CC BY-NC-ND.

关键词： RNA

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Polar jets of swimming bacteria condensed by a patterned liquid crystal

arXiv

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arXiv 2020年

作者： Turiv, Taras Koizumi, Runa Thijssen, Kristian Genkin, Mikhail M. Yu, Hao Peng, Chenhui Wei, Qi-Huo Yeomans, Julia M. Aranson, Igor S. Doostmohammadi, Amin Lavrentovich, Oleg D. Advanced Materials Liquid Crystal Institute Chemical Physics Interdisciplinary Program Kent State University KentOH44242 United States Rudolf Peierls Centre for Theoretical Physics University of Oxford Clarendon Laboratory Parks Rd. OxfordOX1 3PU United Kingdom Cold Spring Harbor Laboratory 1 Bungtown Rd Cold Spring HarborNY11724 United States Department of Physics Kent State University KentOH44242 United States Department of Biomedical Engineering Pennsylvania State University University ParkPA16802 United States

Active matter exhibits remarkable collective behavior in which flows, continuously generated by active particles, are intertwined with the orientational order of these particles. The relationship remains poorly understood as the activity and order are difficult to control independently. Here we demonstrate important facets of this interplay by exploring dynamics of swimming bacteria in a liquid crystalline environment with pre-designed periodic splay and bend in molecular orientation. The bacteria are expelled from the bend regions and condense into polar jets that propagate and transport cargo unidirectionally along the splay regions. The bacterial jets remain stable even when the local concentration exceeds the threshold of bending instability in a non-patterned system. Collective polar propulsion and different role of bend and splay are explained by an advection-diffusion model and by numerical simulations that treat the system as a two-phase active nematic. The ability of prepatterned liquid crystalline medium to streamline the chaotic movements of swimming bacteria into polar jets that can carry cargo along a predesigned trajectory opens the door for potential applications in cell sorting, microscale delivery and soft microrobotics. Copyright © 2020, The Authors. All rights reserved.

关键词： Bacteria

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On the Lagrangian-Eulerian Coupling in the Immersed Finite Element/Difference Method

arXiv

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arXiv 2021年

作者： Lee, Jae H. Griffith, Boyce E. Department of Mathematics University of North Carolina Chapel HillNC United States Department of Mechanical Engineering Johns Hopkins University BaltimoreMD United States Institute for Computational Medicine Johns Hopkins University BaltimoreMD United States Departments of Mathematics Applied Physical Sciences and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina School of Medicine Chapel HillNC United States McAllister Heart Institute University of North Carolina School of Medicine Chapel HillNC United States

The immersed boundary (IB) method is a non-body conforming approach to fluid-structure interaction (FSI) that uses an Eulerian description of the momentum, viscosity, and incompressibility of a coupled fluid-structure system and a Lagrangian description of the deformations, stresses, and resultant forces of the immersed structure. Integral transforms with Dirac delta function kernels couple the Eulerian and Lagrangian variables, and in practice, discretizations of these integral transforms use regularized delta function kernels. Many different kernel functions have been proposed, but prior numerical work investigating the impact of the choice of kernel function on the accuracy of the methodology has often been limited to simplified test cases or Stokes flow conditions that may not reflect the method’s performance in applications, particularly at intermediate-to-high Reynolds numbers, or under different loading conditions. This work systematically studies the effect of the choice of regularized delta function in several fluid-structure interaction benchmark tests using the immersed finite element/difference (IFED) method, which is an extension of the IB method that uses a finite element structural discretizations combined with a Cartesian grid finite difference method for the incompressible Navier-Stokes equations. Whereas the conventional IB method spreads forces from the nodes of the structural mesh and interpolates velocities to those nodes, the IFED formulation evaluates the regularized delta function on a collection of interaction points that can be chosen to be denser than the nodes of the Lagrangian mesh. This opens the possibility of using structural discretizations with wide node spacings that would produce gaps in the Eulerian force in nodally coupled schemes (e.g., if the node spacing is comparable to or broader than the support of the regularized delta function). Earlier work with this methodology suggested that such coarse structural meshes can yield imp

关键词： Fluid structure interaction

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Author Correction: SARS-CoV-2 infection engenders heterogeneous ribonucleoprotein interactions to impede translation elongation in the lungs

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EXPERIMENTAL AND MOLECULAR MEDICINE 2023年第12期55卷 2609-2609页

作者： Kim, Junsoo Youn, Daehwa Choi, Seunghoon Lee, Youn Woo Sumberzul, Dulguun Yoon, Jeongeun Lee, Hanju Bae, Jong Woo Noh, Hyuna On, Dain Hong, Seung-Min An, Se-Hee Jang, Hui Jeong Kim, Seo Yeon Kim, Young Been Hwang, Ji-Yeon Lee, Hyo-Jung Kim, Hong Bin Park, Jun Won Yun, Jun-Won Shin, Jeon-Soo Seo, Jun-Young Nam, Ki Taek Choi, Kang-Seuk Lee, Ho-Young Chang, Hyeshik Seong, Je Kyung Cho, Jun Center for RNA Research Institute for Basic Science (IBS) Seoul National University Seoul Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National University Seoul Republic of Korea Department of Biomedical Science and Engineering Gwangju Institute of Science and Technology (GIST) Gwangju Republic of Korea Korea Mouse Phenotyping Center (KMPC) Seoul National University Seoul Republic of Korea Laboratory of Developmental Biology and Genomics Research Institute for Veterinary Science and BK 21 PLUS Program for Creative Veterinary Science Research College of Veterinary Medicine Seoul National University Seoul Republic of Korea Department of Nuclear Medicine Seoul National University Bundang Hospital Seongnam Republic of Korea School of Biological Sciences Seoul National University Seoul Republic of Korea Laboratory of Avian Diseases Research Institute for Veterinary Science and BK 21 PLUS Program for Creative Veterinary Science Research College of Veterinary Medicine Seoul National University Seoul Republic of Korea Preclinical Research Center Seoul National University Bundang Hospital Seongnam Republic of Korea Department of Periodontology Section of Dentistry Seoul National University Bundang Hospital Seongnam Republic of Korea Department of Internal Medicine Seoul National University Bundang Hospital Seoul National University College of Medicine Seongnam Republic of Korea Division of Biomedical Convergence College of Biomedical Science Kangwon National University ChunCheon Republic of Korea Laboratory of Veterinary Toxicology College of Veterinary Medicine Seoul National University Seoul Republic of Korea Severance Biomedical Science Institute Graduate School of Medical Science Brain Korea 21 Project Yonsei University College of Medicine Seoul Republic of Korea Department of Nuclear Medicine Seoul National University College of Medicine Seoul Republic of Korea Interdisciplinary Program and BIO MAX Institute Seoul National University

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Erratum to: Enzymatic- and temperature-sensitive controlled release of ultrasmall superparamagnetic iron oxides (USPIOs)

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Journal of Nanobiotechnology 2011年第1期9卷 1-1页

作者： Shann S Yu Ryan A Ortega Charleson S Bell Todd D Giorgio Randy L Scherer Conlin P O'Neil Jeffrey A Hubbell Department of Biomedical Engineering Vanderbilt University Nashville Tennessee USA Vanderbilt Institute for Nanoscale Science and Engineering Vanderbilt University Nashville Tennessee USA Interdisciplinary Program in Materials Science Vanderbilt University Nashville Tennessee USA Integrative Biosciences Institute École Polytechnique Fédérale de Lausanne Lausanne Switzerland

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Regulatory considerations for the clinical and research use of transcranial direct current stimulation (tDCS): Review and recommendations from an expert panel

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Clinical Research and Regulatory Affairs 2015年第1期32卷 22-35页

作者： Fregni, F. Nitsche, M.A. Loo, C.K. Brunoni, A.R. Marangolo, P. Leite, J. Carvalho, S. Bolognini, N. Caumo, W. Paik, N.J. Simis, M. Ueda, K. Ekhtiari, H. Luu, P. Tucker, D.M. Tyler, W.J. Brunelin, J. Datta, A. Juan, C.H. Venkatasubramanian, G. Boggio, P.S. Bikson, M. Spaulding Neuromodulation Center Spaulding Rehabilitation Hospital Harvard Medical School Boston MA United States Department of Clinical Neurophysiology Georg-August-University Göttingen Germany School of Psychiatry Black Dog Institute University of New South Wales Sydney Australia Service of Interdisciplinary Neuromodulation Department and Institute of Psychiatry University of São Paulo São Paulo Brazil Department of Experimental and Clinical Medicine University Politecnica Delle Marche Ancona IRCCS Fondazione Santa Lucia Rome Italy School of Psychology (EPsi) University of Minho Campus de Gualtar Braga Portugal Department of Psychology University of Milano Bicocca Milan Italy Laboratory of Neuropsychology IRCC Instituto Auxologico Italiano Milan Italy Laboratory of Pain and Neuromodulation Hospital de Clínicas de Porto Alegre UFRGS Porto Alegre Brazil Department of Rehabilitation Medicine Seoul National University College of Medicine Seoul National University Bundang Hospital Seoul South Korea Institute of Physical Medicine and Rehabilitation Clinics Hospital University of Sao Paulo Medical School Sao Paolo Brazil Division of Neurology Santa Casa Medical School Sao Paulo Brazil National Cardiovascular Center Osaka Japan Translational Neuroscience Program Institute for Cognitive Science Studies Tehran Iran Neurocognitive Laboratory Iranian National Center for Addiction Studies Tehran University of Medical Sciences Tehran Iran Electrical Geodesics Inc. University of Oregon Eugene OR United States Virginia Tech Carilion Research Institute Department of Psychiatry and Behavioral Medicine School of Biomedical Engineering and Sciences Roanoke VA United States EA 4615 Centre Hospitalier le Vinatier Université de Lyon Bron F-69003 France Department of Biomedical Engineering Neural Engineering Laboratory City College of the City University of New York New York NY United States Institute of Cognitive Neuroscience National Central University Taiw

The field of transcranial electrical stimulation (tES) has experienced significant growth in the past 15 years. One of the tES techniques leading this increased interest is transcranial direct current stimulation (tDCS). Significant research efforts have been devoted to determining the clinical potential of tDCS in humans. Despite the promising results obtained with tDCS in basic and clinical neuroscience, further progress has been impeded by a lack of clarity on international regulatory pathways. Therefore, a group of research and clinician experts on tDCS were convened to review the research and clinical use of tDCS. This report reviews the regulatory status of tDCS and summarizes the results according to research, off-label, and compassionate use of tDCS in the following countries: Australia, Brazil, France, Germany, India, Iran, Italy, Portugal, South Korea, Taiwan, and the US. Research use, off label treatment, and compassionate use of tDCS are employed in most of the countries reviewed in this study. It is critical that a global or local effort is organized to pursue definite evidence to either approve and regulate or restrict the use of tDCS in clinical practice on the basis of adequate randomized controlled treatment trials. © 2014 Informa Healthcare USA, Inc. All rights reserved.

关键词： Regulatory Safety TDCS

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A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction

arXiv

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arXiv 2022年

作者： Kolahdouz, Ebrahim M. Wells, David R. Rossi, Simone Aycock, Kenneth I. Craven, Brent A. Griffith, Boyce E. Center for Computational Biology Flatiron Institute Simons Foundation New YorkNY United States Department of Mathematics University of North Carolina Chapel HillNC United States Division of Applied Mechanics Office of Science and Engineering Laboratories Center for Devices and Radiological Health United States Food and Drug Administration Silver SpringMD United States Departments of Mathematics and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel HillNC United States McAllister Heart Institute University of North Carolina Chapel HillNC United States

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressibl

关键词： Fluid structure interaction

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Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks

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Nucleic acids research 2023年第13期51卷 6578-6592页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Bo-Jia Chen Yu-Te Lin Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung 402 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Program in Integrative & Complex Diseases Department of Nutrition Texas A&M University College Station TX 77843 USA. Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

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