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cytoNet: Spatiotemporal network analysis of cell communities (vol 18, e1009846, 2022)

PLOS COMPUTATIONAL BIOLOGY 2022年第11期18卷 e1009846页

作者： Mahadevan, A. S. Long, B. L. Hu, C. W. Ryan, D. T. Grandel, N. E. Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania United States of America. Department of Bioengineering Rice University Houston Texas United States of America. Systems Synthetic and Physical Biology Program Rice University Houston Texas United States of America. Department of Biomedical Engineering University of Texas at San Antonio San Antonio Texas United States of America. Biophysics Graduate Program University of California Berkeley California United States of America. Department of Oral & Maxillofacial Surgery University of Texas Health Science Center at San Antonio San Antonio Texas United States of America. Department of Electrical and Computer Engineering Rice University Houston Texas United States of America.

We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. We demonstrate cytoNet's capabilities in four case studies: 1) characterizing the temporal dynamics of neural progenitor cell communities during neural differentiation, 2) identifying communities of pain-sensing neurons in vivo, 3) capturing the effect of cell community on endothelial cell morphology, and 4) investigating the effect of laminin α4 on perivascular niches in adipose tissue. The analytical framework introduced here can be used to study the dynamics of complex cell communities in a quantitative manner, leading to a deeper understanding of environmental effects on cellular behavior. The versatile, cloud-based format of cytoNet makes the image analysis framework accessible to researchers across domains.

关键词： Calcium imaging Fluorescence imaging Growth factors Centrality Cell cycle and cell division Endothelial cells Network analysis Stem cells

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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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Observation of Colossal Terahertz Magnetoresistance and Magnetocapacitance in a Perovskite Manganite

arXiv

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arXiv 2023年

作者： Tay, Fuyang Chaudhary, Swati He, Jiaming Peraca, Nicolas Marquez Baydin, Andrey Fiete, Gregory A. Zhou, Jianshi Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Physics University of Texas at Austin AustinTX78712 United States Department of Physics Northeastern University BostonMA02115 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Materials Science and Engineering Program Mechanical Engineering University of Texas at Austin AustinTX78712 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

We have studied the terahertz response of a bulk single crystal of La0.875Sr0.125MnO3at around its Curie temperature, observing large changes in the real and imaginary parts of the optical conductivity as a function of magnetic field. The terahertz resistance and capacitance extracted from the optical conductivity rapidly increased with increasing magnetic field and did not show any sign of saturation up to 6 T, reaching 60% and 15%, respectively, at 180 K. The observed terahertz colossal magnetoresistance and magnetocapacitance effects can be qualitatively explained by using a two-component model that assumes the coexistence of two phases with vastly different conductivities. These results demonstrate the potential use of perovskite manganites for developing efficient terahertz devices based on magnetic modulations of the amplitude and phase of terahertz waves. Copyright © 2023, The Authors. All rights reserved.

关键词： Optical conductivity

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Homogenization and design of acoustic Willis metasurfaces

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Physical Review B 2021年第5期103卷 054306-054306页

作者： Hussein Esfahlani Yarden Mazor Andrea Alù Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Kymeta Corporation Redmond Washington 98052 USA Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Physics Program Graduate Center of the City University of New York New York New York 10016 USA

Metasurfaces are ultrathin planar arrays of carefully tailored subwavelength particles that enable agile and flexible manipulation of the impinging waves. Originally introduced in optics, their application to acoustic waves has recently opened exciting opportunities for exotic sound control. In conventional acoustic inclusions, the interactions with the impinging pressure and velocity are decoupled, limiting the functionalities that arrays of them can achieve. While the coupling between these two quantities in symmetry-breaking inclusions, known as Willis coupling, has been discussed for several years, only recently has it been realized that these phenomena can become nonperturbative in suitably tailored resonant scatterers. Here, we explore the opportunities that these Willis meta-atoms open in the context of acoustic metasurfaces, offering additional knobs to manipulate and tailor sound. The general response of Willis metasurface is analytically derived, yielding fundamental bounds and optimal surface responses enabling full control of the impinging acoustic wave front.

关键词： Acoustic metamaterials Acoustic wave phenomena Polarizability

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Controlled synthetic chirality in macroscopic assemblies of carbon nanotubes

arXiv

引用

arXiv 2023年

作者： Doumani, Jacques Lou, Minhan Dewey, Oliver Hong, Nina Fan, Jichao Baydin, Andrey Yomogida, Yohei Yanagi, Kazuhiro Pasquali, Matteo Saito, Riichiro Kono, Junichiro Gao, Weilu Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX United States Department of Electrical and Computer Engineering The University of Utah Salt Lake CityUT United States Carbon Hub Rice University HoustonTX United States Department of Chemical and Biomolecular Engineering Rice University HoustonTX United States J.A. Woollam Co. Inc. LincolnNE United States Smalley–Curl Institute Rice University HoustonTX United States Department of Physics Tokyo Metropolitan University Tokyo Japan Department of Chemistry Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States Department of Physics Tohoku University Sendai Japan Department Physics and Astronomy Rice University HoustonTX United States

There is an emerging recognition that successful utilization of chiral degrees of freedom can bring new scientific and technological opportunities to diverse research areas. Hence, methods are being sought for creating artificial matter with controllable chirality in an uncomplicated and reproducible manner. Here, we report the development of two straightforward methods for fabricating wafer-scale chiral architectures of ordered carbon nanotubes (CNTs) with tunable and giant circular dichroism (CD). Both methods employ simple approaches, (i) mechanical rotation and (ii) twist-stacking, based on controlled vacuum filtration and do not involve any sophisticated nanofabrication processes. We used a racemic mixture of CNTs as the starting material, so the intrinsic chirality of chiral CNTs is not responsible for the observed chirality. In particular, by controlling the stacking angle and handedness in (ii), we were able to maximize the CD response and achieve a record-high deep-ultraviolet ellipticity of 40 ± 1 mdeg/nm. Our theoretical simulations using the transfer matrix method reproduce the salient features of the experimentally observed CD spectra and further predict that a film of twist-stacked CNTs with an optimized thickness will exhibit an ellipticity as high as 150 mdeg/nm. The created wafer-scale objects represent a new class of synthetic chiral matter consisting of ordered quantum wires whose macroscopic properties are governed by nanoscopic electronic signatures such as van Hove singularities. These artificial structures with engineered chirality will not only provide playgrounds for uncovering new chiral phenomena but also open up new opportunities for developing high-performance chiral photonic and optoelectronic devices. © 2023, CC BY.

关键词： Carbon nanotubes

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Magnetically tuned continuous transition from weak to strong coupling in terahertz magnon polaritons

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Physical Review Research 2023年第1期5卷 L012039-L012039页

作者： Andrey Baydin Kenji Hayashida Takuma Makihara Fuyang Tay Xiaoxuan Ma Wei Ren Guohong Ma G. Timothy Noe, II Ikufumi Katayama Jun Takeda Hiroyuki Nojiri Shixun Cao Motoaki Bamba Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Smalley-Curl Institute Rice University Houston Texas 77005 USA Division of Applied Physics Graduate School of Engineering Hokkaido University Sapporo Hokkaido 060-8628 Japan Department of Physics and Astronomy Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA Department of Physics International Center of Quantum and Molecular Structures and Materials Genome Institute Shanghai University 200444 Shanghai China Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama 240-8501 Japan Institute for Materials Research Tohoku University Sendai 980-8577 Japan The Hakubi Center for Advanced Research Kyoto University Kyoto 606-8502 Japan Department of Physics I Kyoto University Kyoto 606-8502 Japan PRESTO Japan Science and Technology Agency Kawaguchi 332-0012 Japan Department of Materials Science and NanoEngineering Rice University Houston Texas 77005 USA

Depending on the relative rates of coupling and dissipation, a light-matter coupled system is either in the weak- or strong-coupling regime. Here, we present a unique system where the coupling rate continuously increases with an externally applied magnetic field while the dissipation rate remains constant, allowing us to monitor a weak-to-strong coupling transition as a function of magnetic field. We observed a Rabi splitting of a terahertz magnon mode in yttrium orthoferrite above a threshold magnetic field of ∼14 T. Based on a microscopic theoretical model, we show that with increasing magnetic field the magnons transition into magnon polaritons through an exceptional point, which will open up new opportunities for in situ control of non-Hermitian systems.

关键词： Antiferromagnetism High magnetic fields Magneto-optics Magnons Polaritons Non-Hermitean systems Terahertz time-domain spectroscopy Transfer matrix method

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Neural population dynamics in songbird RA and HVC during learned motor-vocal behavior

arXiv

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arXiv 2024年

作者： Tostado-Marcos, Pablo Arneodo, Ezequiel M. Ostrowski, Lauren Brown, Daril E. Perez, Xavier A. Kadwory, Adam Stanwicks, Lauren L. Alothman, Abdullah Gentner, Timothy Q. Gilja, Vikash Department of Bioengineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Electrical and Computer Engineering University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Psychology University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Neurobiology University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States Neurosciences Graduate Program University of California San Diego 9500 Gilman Drive La Jolla CA92093 United States

Complex, learned motor behaviors involve the coordination of large-scale neural activity across multiple brain regions, but our understanding of the population-level dynamics within different regions tied to the same behavior remains limited. Here, we investigate the neural population dynamics underlying learned vocal production in awake-singing songbirds. We use Neuropixels probes to record the simultaneous extracellular activity of populations of neurons in two regions of the vocal motor pathway. In line with observations made in non-human primates during limb-based motor tasks, we show that the population-level activity in both the premotor nucleus HVC and the motor nucleus RA is organized on low-dimensional neural manifolds upon which coordinated neural activity is well described by temporally structured trajectories during singing behavior. Both the HVC and RA latent trajectories provide relevant information to predict vocal sequence transitions between song syllables. However, the dynamics of these latent trajectories differ between regions. Our state-space models suggest a unique and continuous-over-time correspondence between the latent space of RA and vocal output, whereas the corresponding relationship for HVC exhibits a higher degree of neural variability. We then demonstrate that comparable high-fidelity reconstruction of continuous vocal outputs can be achieved from HVC and RA neural latents and spiking activity. Unlike those that use spiking activity, however, decoding models using neural latents generalize to novel sub-populations in each region, consistent with the existence of preserved manifolds that confine vocal-motor activity in HVC and RA. © 2024, CC BY.

关键词： Dynamics

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A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation

arXiv

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arXiv 2022年

作者： Yang, Zhenyu Hu, Zongsheng Ji, Hangjie Lafata, Kyle Floyd, Scott Yin, Fang-Fang Wang, Chunhao Deparment of Radiation Oncology Duke University DurhamNC27710 United States Medical Physics Graduate Program Duke Kunshan University Jiangsu Kunshan215316 China Department of Mathematics North Carolina State University RaleighNC27695 United States Department of Radiology Duke University DurhamNC27710 United States Department of Electrical and Computer Engineering Duke University DurhamNC27710 United States

Purpose: To develop a neural ordinary differential equation (ODE) model for visualizing deep neural network behavior during multi-parametric MRI (mp-MRI) based glioma segmentation as a method to enhance deep learning explainability. Methods: By hypothesizing that deep feature extraction can be modeled as a spatiotemporally continuous process, we designed a novel deep learning model, neural ODE, in which deep feature extraction was governed by an ODE without explicit expression. The dynamics of 1) MR images after interactions with the deep neural network and 2) segmentation formation can thus be visualized after solving ODE. An accumulative contribution curve (ACC) was designed to quantitatively evaluate each MR image's utilization by the deep neural network towards the final segmentation results. The proposed neural ODE model was demonstrated using 369 glioma patients with a 4-modality mp-MRI protocol: T1, contrast-enhanced T1 (T1-Ce), T2, and FLAIR. Three neural ODE models were trained to segment enhancing tumor (ET), tumor core (TC), and whole tumor (WT), respectively. The key MR modalities with significant utilization by deep neural network were identified based on ACC analysis. Segmentation results by deep neural networks using only the key MR modalities were compared to the ones using all 4 MR modalities in terms of Dice coefficient, accuracy, sensitivity, and specificity. Results: All neural ODE models successfully illustrated image dynamics as expected. ACC analysis identified T1-Ce as the only key modality in ET and TC segmentations, while both FLAIR and T2 were key modalities in WT segmentation. Compared to the U-Net results using all 4 MR modalities, Dice coefficient of ET (0.784→0.775), TC (0.760→0.758), and WT (0.841→0.837) using the key modalities only had minimal differences without significance. Accuracy, sensitivity, and specificity results demonstrated the same patterns. Conclusion: The neural ODE model offers a new tool for optimizing the deep lear

关键词： Tumors

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Thermalization of fluorescent protein exciton-polaritons at room temperature

arXiv

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arXiv 2022年

作者： Satapathy, Sitakanta Liu, Bin Deshmukh, Prathmesh Molinaro, Paul M. Dirnberger, Florian Khatoniar, Mandeep Koder, Ronald L. Menon, Vinod M. Department of Physics Center for Discovery and Innovation The City College of New York 85 St. Nicholas Terrace New YorkNY10031 United States The PhD Program in Physics The Graduate Center of the City University of New York 365 5th Ave New YorkNY10016 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

Fluorescent proteins (FPs) have recently emerged as a serious contender for realizing ultra-low threshold room temperature exciton-polariton condensation and lasing. Our contribution investigates the thermalization of FP microcavity exciton-polaritons upon optical pumping under ambient conditions. We realize polariton cooling using a new FP molecule, called mScarlet, coupled strongly to the optical modes in a Fabry-Pérot cavity. Interestingly, at the threshold excitation energy (fluence) of ~9 nJ/pulse (15.6 mJ/cm2), we observe an effective temperature, Teff ~350 ± 35 K close to the lattice temperature indicative of strongly thermalized exciton-polaritons at equilibrium. This efficient thermalization results from the interplay of radiative pumping facilitated by the energetics of the lower polariton branch and the cavity Qfactor. Direct evidence for dramatic switching from an equilibrium state into a metastable state is observed for the organic cavity polariton device at room temperature via deviation from the Maxwell-Boltzmann statistics at k1 = 0 above the threshold. Thermalized polariton gases in organic systems at equilibrium hold substantial promise for designing room temperature polaritonic circuits, switches, and lattices for analog simulation. © 2022, CC BY-NC-SA.

关键词： Polariton

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Set-based state estimation and fault diagnosis of linear discrete-time descriptor systems using constrained zonotopes

arXiv

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arXiv 2020年

作者： Rego, Brenner S. Raimondo, Davide M. Raffo, Guilherme V. Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte Brazil Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Department of Electronics Engineering Federal University of Minas Gerais Belo Horizonte Brazil

This paper presents new methods for set-valued state estimation and active fault diagnosis of linear descriptor systems. The algorithms are based on constrained zonotopes, a generalization of zonotopes capable of describing strongly asymmetric convex sets, while retaining the computational advantages of zonotopes. Additionally, unlike other set representations like intervals, zonotopes, ellipsoids, paralletopes, among others, linear static constraints on the state variables, typical of descriptor systems, can be directly incorporated in the mathematical description of constrained zonotopes. Therefore, the proposed methods lead to more accurate results in state estimation in comparison to existing methods based on the previous sets without requiring rank assumptions on the structure of the descriptor system and with a fair trade-off between accuracy and efficiency. These advantages are highlighted in two numerical examples. Copyright © 2020, The Authors. All rights reserved.

关键词： Failure analysis

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