Advanced Research Computing

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Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System through Geometric Feature Learning
Zhang, Chaoyu; Shi, Shanghao; Wang, Ning; Xu, Xiangxiang; Li, Shaoyu; Zheng, Lizhong; Marchany, Randy; Gardner, Mark; Hou, Y. Thomas; Lou, Wenjing (ACM, 2024-10-14)
Anomaly-Based Intrusion Detection Systems (IDSs) have been extensively researched for their ability to detect zero-day attacks. These systems establish a baseline of normal behavior using benign traffic data and flag deviations from this norm as potential threats. They generally experience higher false alarm rates than signature-based IDSs. Unlike image data, where the observed features provide immediate utility, raw network traffic necessitates additional processing for effective detection. It is challenging to learn useful patterns directly from raw traffic data or simple traffic statistics (e.g., connection duration, package inter-arrival time) as the complex relationships are difficult to distinguish. Therefore, some feature engineering becomes imperative to extract and transform raw data into new feature representations that can directly improve the detection capability and reduce the false positive rate. We propose a geometric feature learning method to optimize the feature extraction process. We employ contrastive feature learning to learn a feature space where normal traffic instances reside in a compact cluster. We further utilize H-Score feature learning to maximize the compactness of the cluster representing the normal behavior, enhancing the subsequent anomaly detection performance. Our evaluations using the NSL-KDD and N-BaloT datasets demonstrate that the proposed IDS powered by feature learning can consistently outperform state-of-the-art anomaly-based IDS methods by significantly lowering the false positive rate. Furthermore, we deploy the proposed IDS on a Raspberry Pi 4 and demonstrate its applicability on resource-constrained Internet of Things (IoT) devices, highlighting its versatility for diverse application scenarios.
Prompt Engineering for X3D Object Creation with LLMs
Polys, Nicholas; Mohammed, Ayat; Sandbrook, Ben (ACM, 2024-09-25)
Large Language Models (LLMs) are a new class of knowledge embodied in a computer and trained on massive amounts of human text, image, and video examples. As the result of a user prompt, these LLMs can generate generally coherent responses in several kinds of media and languages. Can LLMs write X3D code? In this paper we explore the ability of several leading LLMs to generate valid and sensible code for interactive X3D scenes. We compare the prompt results from three different LLMs to examine the quality of the generated X3D. We setup an experimental framework that uses a within-subjects repeated-measures design to create X3D from text prompts. We vary our prompt strategies and give the LLMs increasingly challenging and increasingly detailed scene requests.We assess the quality of the resulting X3D scenes including geometry, appearances, animations, and interactions. Our results provide a comparison of different prompt strategies and their outcomes. Such results provide early probes into the limited epistemology and fluency of contemporary LLMs in composing multi-part, animate-able 3D objects.
Enhancing Brain Flow Visualization with Automated 3D Data Processing: A Study on DCE-MRI Data from Mice with Tumors
Mohammed, Ayat; Polys, Nicholas F.; Cunningham, Jessica; Munson, Jennifer M.; Chutkowski, James; Liang, Hun; Park, Daniel; Rockne, Russell; Woodall, Ryan; Esparza, Cora (ACM, 2023-10-09)
Enhancing the process of generating entirely automated visualization schemes of complex fluid flow patterns within brain tumors is critical for gaining insights into their movements and behaviors. This study focused on optimizing and automating the processing of 3D volumetric and vector field data sets obtained from DCE-MRI (Dynamic Contrast-Enhanced Magnetic Resonance Imaging) scans. It is crucial to maintain performance, preserve data quality and resolution, and provide an accessible platform for biomedical scientists. In this paper, we represent an innovative approach to enhance fluid flow visualization of brain tumors through scalable visualization techniques. New techniques have been designed, benchmarked, and authenticated to produce X3D visualizations in Web3D environments using Python, and ParaView. The proposed approach does not only enhance fluid flow visualization in the context of brain tumor research but also provides a reproducible and transparent framework for future studies with both human and mouse scans.
Immersive Cross-platform X3D Training: Elevating Construction Safety Education
Roofigari-Esfahan, Nazila; Polys, Nicholas F.; Johnson, Ashley; Ogle, J. Todd; Sandbrook, Ben (ACM, 2023-10-09)
A multi-platform Virtual Reality (VR) approach is proposed to complement the traditional approaches for construction safety training. Visual simulations of a highway construction project were developed and presented through the developed platforms, aiming at giving students immersive experience of actual construction environments. The simulated worksite scenarios included active traffic, multiple worker roles and heavy equipment, and was rendered at different times of day and weather conditions. We used this material in an undergraduate class activity with 50 students. During a session in our visualization lab, students experienced the scenarios presenting day shift, afternoon shift with adverse weather and night shift and were asked to develop daily report of their job site observation. The scenrios were presented via the following platforms: TV projection, Mobile Phone, Head-Mounted Display (HMD), and CAVE projection room. The results demonstrates that the multi-platform immersive experience has the potential to significantly improve hazard recognition skill of construction students.
Building 3D Web Interoperability for the Metaverse
Havele, Anita; Polys, Nicholas F.; Behr, Johannes (ACM, 2023-10-09)
This workshop brings together participants from around the world with the goal of building a strong foundation for an open, interoperable Metaverse using the Web and the Web Standards ecosystem. The workshop will focus on four main topics: 1) The variety of relevant Standards and technology roles in the Metaverse stack, 2) the role of the 3D Web Interoperability Working Group, which has recently been chartered in the Metaverse Standards Forum, 3) scoping what the Metaverse IS NOT, and 4) how Use Cases and Scenarios can help clarify what the Metaverse IS. In this emerging space, perspectives and tradeoffs abound; we hope this workshop will push our understanding and terminology forward and also provide the community with an actionable set of common (yet extensible) referents and goals.
Integrating XR Content in X3DOM: Supporting Navigation and Custom Functions in X3D Scenes
Sethi, Raghav; Plesch, Andreas; Sturm, Timo; Polys, Nicholas F. (ACM, 2023-10-09)
This paper explores the integration of eXtended Reality (XR) content within X3DOM, a popular framework for displaying 3D content in web browsers. The importance ofWeb3D and the prevalent use of the X3D file format are discussed. With the deprecation of WebVR and the adoption ofWebXR in web browsers, X3DOM has emerged as one of the pioneering adaptors of WebXR APIs. This paper highlights the current capabilities of X3DOM, which enable users to explore 3D scenes on regular screens and seamlessly transition into Virtual Reality (VR) mode. It showcases the use of controllers for navigation and the execution of custom functions within the X3D scenes. Additionally, the paper presents a series of developed 3D scenes that demonstrate the effectiveness of X3DOM in rendering VR content, ranging from indoor to outdoor environments, utilizing X3D nodes to display images and videos to create immersive photospheres and rich interactive scenes.
Increasing Web3D Accessibility with Audio Captioning
Polys, Nicholas F.; Wasi, Sheeban Mohd (ACM, 2023-10-09)
Situational awareness plays a critical role in daily life, enabling individuals to comprehend their surroundings, make informed decisions, and navigate safely. However, individuals with low vision or visual impairments face difficulties in perceiving their real or virtual environment. In order to address this challenge, we propose a 3D computer vision-based accessibility solution, empowered by object-detection and text-to-speech technology. Our application describes the visual content of a Web3D scene from the user’s perspective through auditory channels, thereby enhancing situational awareness for individuals with visual impairments in virtual and physical environments. We conducted a user study of 44 participants to compare a set of algorithms for specific tasks, such as Search or Summarize, and assessed the effectiveness of our captioning algorithms based on user ratings of naturalness, correctness, and satisfaction. Our study results indicate positive subjective results in accessibility for both normal and visually-impaired subjects and also distinguish significant effects between the task and the captioning algorithm.
Designing for Social Interactions in a Virtual Art Gallery
Polys, Nicholas F.; Roshan, Samridhi; Newton, Emily; Narula, Muskaan; Thai, Bao-Tran (ACM, 2022-11-02)
The dawn of a new digital world has emerged with new ways to communicate and collaborate with other people across the globe. Metaverses and Mirror Worlds have broadened our perspectives on the ways we can utilize 3D virtual environments. A Mirror World is a 3D virtual space that depicts a real-life place or environment that people may want to see physically or would like to manipulate to create something new. A perfect example of this would be an art gallery which provides people an outlet to express themselves through various art forms and be able to socialize and have that human interaction that is needed during times when physical presence may be difficult. This project strives to improve user social interactions and make spatial control easier and more fluid in a virtual art gallery, while also incorporating the existing metaphor of permission and user privileges used in synchronous collaborative environments. We worked to create ways for people to be invited into group chats based on proximity, allowing users to give their consent as to who they want to talk to and who they will allow to share control within the space. We also implemented a way to view the space as a 3D map that highlights pieces of artwork around the space for people to teleport to and view at ease. To demonstrate this shared viewing and navigation experience we also focused on incorporating audio and spatial interaction features within the art gallery prototype of X3D and glTF models, images and audio, and HTML user interface.
The Keys to an Open, Interoperable Metaverse
Havele, Anita; Brutzman, Donald; Benman, William; Polys, Nicholas F. (ACM, 2022-11-02)
The term ‘Metaverse’ has taken on new interest recently, appearing prominently in the marketing materials of a number of large technology companies. Indeed, many have attempted, or are attempting, to co-opt it for their own purposes, which has resulted in a great deal of confusion among producers and consumers in the marketplace. With this paper, theWeb3D Consortium seeks to address this confusion by exploring the history of the ‘Metaverse’, provide a workable definition of the term ‘Metaverse’, and provide a vision for its sustainable, cooperative construction into the future.We believe that all the technologies are in place to fulfill the vision of an open, equitable, and ubiquitous information space. What remains are the key issues that have kept the Metaverse from manifesting the last two decades: poor user experience and poor corporate cooperation.
Spatial Audio Designer
Polys, Nicholas F.; Bendelac, Noam (ACM, 2022-11-02)
The Web Audio API is an underutilized technology that provides a potential for rich interactive control over sound generation and rendering. Our team made use of the API in combination with Web3D technologies to create a spatial audio design tool for digital audiovisual creators. Our primary design challenge was creating an interface for visualizing and manipulating sound design in 3D space. We wanted our interface to be learnable and usable for our target user groups: digital music creators, digital audiovisual 3D artists, and physical audiovisual installation artists who wish to develop ideas in a virtual space. From user interviews, we learned that users needed a detailed visual 3D space as a starting point to populate with sound, as well as fine control over positioning of sound sources. The prototype web app can be used by digital and physical artists to create novel virtual audiovisual experiences, or to model a physical audiovisual installation to share and test with others. More work needs to be done to add direct spatial controls for sound fields and to make the app more natural to use. We asked artists of varying technical skill to use the app and re-create a reference scene, and measured how accurate their re-creation is.
X3D Field Trips for Remote Learning
Polys, Nicholas F.; Meaney, Kathleen; Munsell, John F.; Addlestone, Benjamin J. (ACM, 2021-11-08)
Combinations of immersive media and graphic portrayals can enable the human subjective sense of Presence. This paper collects our experiences and evaluations from six projects that use Extensible 3D (X3D) interactive graphics to deliver spatial experiences across the WWW. X3D enables the combination of spherical panoramas with 3D models and maps to visually transport users to a specific real location at a specific time. Remote users have access to these worlds through a Web-browser or other immersive device; local users in a CAVE can collaborate with natural physical gestures; . We reflect on the graphical and interactive requirements of these projects and provide guidance for future applications. In the face of physical lock-downs and distancing due to the CoVID pandemic, such platforms illustrate the opportunities and challenges in the design and delivery of spatial visualizations, especially for remote learning.
Effect of Topology and Geometric Structure on Collective Motion in the Vicsek Model
McClure, James E.; Abaid, Nicole (Frontiers, 2022-03-08)
In this work, we explore how the emergence of collective motion in a system of particles is influenced by the structure of their domain. Using the Vicsek model to generate flocking, we simulate two-dimensional systems that are confined based on varying obstacle arrangements. The presence of obstacles alters the topological structure of the domain where collective motion occurs, which, in turn, alters the scaling behavior. We evaluate these trends by considering the scaling exponent and critical noise threshold for the Vicsek model, as well as the associated diffusion properties of the system. We show that obstacles tend to inhibit collective motion by forcing particles to traverse the system based on curved trajectories that reflect the domain topology. Our results highlight key challenges related to the development of a more comprehensive understanding of geometric structure's influence on collective behavior.
Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)
Ramsey, Jolene; McIntosh, Brenley; Renfro, Daniel; Aleksander, Suzanne A.; LaBonte, Sandra; Ross, Curtis; Zweifel, Adrienne E.; Liles, Nathan; Farrar, Shabnam; Gill, Jason J.; Erill, Ivan; Ades, Sarah; Berardini, Tanya Z.; Bennett, Jennifer A.; Brady, Siobhan; Britton, Robert; Carbon, Seth; Caruso, Steven M.; Clements, Dave; Dalia, Ritu; Defelice, Meredith; Doyle, Erin L.; Friedberg, Iddo; Gurney, Susan M. R.; Hughes, Lee; Johnson, Allison; Kowalski, Jason M.; Li, Donghui; Lovering, Ruth C.; Mans, Tamara L.; McCarthy, Fiona; Moore, Sean D.; Murphy, Rebecca; Paustian, Timothy D.; Perdue, Sarah; Peterson, Celeste N.; Pruss, Birgit M.; Saha, Margaret S.; Sheehy, Robert R.; Tansey, John T.; Temple, Louise; Thorman, Alexander William; Trevino, Saul; Vollmer, Amy Cheng; Walbot, Virginia; Willey, Joanne; Siegele, Deborah A.; Hu, James C. (2021-10)
Author summary The primary scientific literature catalogs the results from publicly funded scientific research about gene function in human-readable format. Information captured from those studies in a widely adopted, machine-readable standard format comes in the form of Gene Ontology (GO) annotations about gene functions from all domains of life. Manual annotations based on inferences directly from the scientific literature, including the evidence used to make such inferences, represent the best return on investment by improving data accessibility across the biological sciences and allowing novel insights between evolutionarily related organisms. To supplement professional curation, our Community Assessment of Community Annotation with Ontologies (CACAO) project enabled annotation of the scientific literature by community annotators, in this case undergraduates, which resulted in the contribution of thousands of unique, validated entries to public resources. Importantly, the annotations described here initiated by nonexperts often deal with topics not typically covered by the experts. These annotations are now being used by scientists worldwide in their research efforts. Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.
Neural network based pore flow field prediction in porous media using super resolution
Zhou, Xu-Hui X.; McClure, James; Chen, Cheng; Xiao, Heng (2021)
Previous works have demonstrated using the geometry of the microstructure of porous media to predict the ow velocity fields therein based on neural networks. However, such schemes are purely based on geometric information without accounting for the physical constraints on the velocity fields such as that due to mass conservation. In this work, we propose using a super-resolution technique to enhance the velocity field prediction by utilizing coarse-mesh velocity fields, which are often available inexpensively but carry important physical constraints. We apply our method to predict velocity fields in complex porous media. The results demonstrate that incorporating the coarse-mesh flow field significantly improves the prediction accuracy of the fine-mesh flow field as compared to predictions that rely on geometric information alone. This study highlights the merits of including coarse-mesh flow field with physical constraints embedded in it.
Approximating Community Water System Service Areas to Explore the Demographics of SDWA Compliance in Virginia
Marcillo, Cristina; Krometis, Leigh-Anne H.; Krometis, Justin (MDPI, 2021-12-16)
Although the United States Safe Drinking Water Act (SDWA) theoretically ensures drinking water quality, recent studies have questioned the reliability and equity associated with community water system (CWS) service. This study aimed to identify SDWA violation differences (i.e., monitoring and reporting (MR) and health-based (HB)) between Virginia CWSs given associated service demographics, rurality, and system characteristics. A novel geospatial methodology delineated CWS service areas at the zip code scale to connect 2000 US Census demographics with 2006–2016 SDWA violations, with significant associations determined via negative binomial regression. The proportion of Black Americans within a service area was positively associated with the likelihood of HB violations. This effort supports the need for further investigation of racial and socioeconomic disparities in access to safe drinking water within the United States in particular and offers a geospatial strategy to explore demographics in other settings where data on infrastructure extents are limited. Further interdisciplinary efforts at multiple scales are necessary to identify the entwined causes for differential risks in adverse drinking water quality exposures and would be substantially strengthened by the mapping of official CWS service boundaries.
Genome-wide identification of enhancers and transcription factors regulating the myogenic differentiation of bovine satellite cells
Lyu, Pengcheng; Settlage, Robert E.; Jiang, Honglin (2021-12-16)
Background Satellite cells are the myogenic precursor cells in adult skeletal muscle. The objective of this study was to identify enhancers and transcription factors that regulate gene expression during the differentiation of bovine satellite cells into myotubes. Results Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) was performed to identify genomic regions where lysine 27 of H3 histone is acetylated (H3K27ac), i.e., active enhancers, from bovine satellite cells before and during differentiation into myotubes. A total of 19,027 and 47,669 H3K27ac-marked enhancers were consistently identified from two biological replicates of before- and during-differentiation bovine satellite cells, respectively. Of these enhancers, 5882 were specific to before-differentiation, 35,723 to during-differentiation, and 13,199 common to before- and during-differentiation bovine satellite cells. Whereas most of the before- or during-differentiation-specific H3K27ac-marked enhancers were located distally to the transcription start site, the enhancers common to before- and during-differentiation were located both distally and proximally to the transcription start site. The three sets of H3K27ac-marked enhancers were associated with functionally different genes and enriched with different transcription factor binding sites. Specifically, many of the H3K27ac-marked enhancers specific to during-differentiation bovine satellite cells were associated with genes involved in muscle structure and development, and were enriched with binding sites for the MyoD, AP-1, KLF, TEAD, and MEF2 families of transcription factors. A positive role was validated for Fos and FosB, two AP-1 family transcription factors, in the differentiation of bovine satellite cells into myotubes by siRNA-mediated knockdown. Conclusions Tens of thousands of H3K27ac-marked active enhancers have been identified from bovine satellite cells before or during differentiation. These enhancers contain binding sites not only for transcription factors whose role in satellite cell differentiation is well known but also for transcription factors whose role in satellite cell differentiation is unknown. These enhancers and transcription factors are valuable resources for understanding the complex mechanism that mediates gene expression during satellite cell differentiation. Because satellite cell differentiation is a key step in skeletal muscle growth, the enhancers, the transcription factors, and their target genes identified in this study are also valuable resources for identifying and interpreting skeletal muscle trait-associated DNA variants in cattle.
A database of global coastal conditions
Castaneda-Guzman, Mariana; Mantilla-Saltos, Gabriel; Murray, Kris A.; Settlage, Robert; Escobar, Luis E. (2021-11-26)
Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth's surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.
The Beginning of the End: A Chromosomal Assembly of the New World Malaria Mosquito Ends with a Novel Telomere
Compton, Austin; Liang, Jiangtao; Chen, Chujia; Lukyanchikova, Varvara; Qi, Yumin; Potters, Mark B.; Settlage, Robert; Miller, Dustin; Deschamps, Stephane; Mao, Chunhong; Llaca, Victor; Sharakhov, Igor V.; Tu, Zhijian Jake (Genetics Society of America, 2020-10-01)
Chromosome level assemblies are accumulating in various taxonomic groups including mosquitoes. However, even in the few reference-quality mosquito assemblies, a significant portion of the heterochromatic regions including telomeres remain unresolved. Here we produce a de novo assembly of the New World malaria mosquito, Anopheles albimanus by integrating Oxford Nanopore sequencing, Illumina, Hi-C and optical mapping. This 172.6 Mbps female assembly, which we call AalbS3, is obtained by scaffolding polished large contigs (contig N50 = 13.7 Mbps) into three chromosomes. All chromosome arms end with telomeric repeats, which is the first in mosquito assemblies and represents a significant step toward the completion of a genome assembly. These telomeres consist of tandem repeats of a novel 30-32 bp Telomeric Repeat Unit (TRU) and are confirmed by analyzing the termini of long reads and through both chromosomal in situ hybridization and a Bal31 sensitivity assay. The AalbS3 assembly included previously uncharacterized centromeric and rDNA clusters and more than doubled the content of transposable elements and other repetitive sequences. This telomere-to-telomere assembly, although still containing gaps, represents a significant step toward resolving biologically important but previously hidden genomic components. The comparison of different scaffolding methods will also inform future efforts to obtain reference-quality genomes for other mosquito species.
Deficiency in the endocytic adaptor proteins PHETA1/2 impairs renal and craniofacial development
Ates, Kristin M.; Wang, Tong; Moreland, Trevor; Veeranan-Karmegam, Rajalakshmi; Ma, Manxiu; Jeter, Chelsi; Anand, Priya; Wenzel, Wolfgang; Kim, Hyung-Goo; Wolfe, Lynne A.; Stephen, Joshi; Adams, David R.; Markello, Thomas; Tifft, Cynthia J.; Settlage, Robert E.; Gahl, William A.; Gonsalvez, Graydon B.; Malicdan, May Christine; Flanagan-Steet, Heather; Pan, Yuchin Albert (2020-05)
A critical barrier in the treatment of endosomal and lysosomal diseases is the lack of understanding of the in vivo functions of the putative causative genes. We addressed this by investigating a key pair of endocytic adaptor proteins, PH domain-containing endocytic trafficking adaptor 1 and 2 (PHETA1/2; also known as FAM109A/B, Ses1/2, IPIP27A/B), which interact with the protein product of OCRL, the causative gene for Lowe syndrome. Here, we conducted the first study of PHETA1/2 in vivo, utilizing the zebrafish system. We found that impairment of both zebrafish orthologs, phetal and pheta2, disrupted endocytosis and ciliogenesis in renal tissues. In addition, pheta1/2 mutant animals exhibited reduced jaw size and delayed chondrocyte differentiation, indicating a role in craniofacial development. Deficiency of pheta1/2 resulted in dysregulation of cathepsin K, which led to an increased abundance of type II collagen in craniofacial cartilages, a marker of immature cartilage extracellular matrix. Cathepsin K inhibition rescued the craniofacial phenotypes in the pheta1/2 double mutants. The abnormal renal and craniofacial phenotypes in the pheta1/2 mutant animals were consistent with the clinical presentation of a patient with a de novo arginine (R) to cysteine (C) variant (R6C) of PHETA1. Expressing the patient-specific variant in zebrafish exacerbated craniofacial deficits, suggesting that the R6C allele acts in a dominant-negative manner. Together, these results provide insights into the in vivo roles of PHETA1/2 and suggest that the R6C variant is contributory to the pathogenesis of disease in the patient. This article has an associated First Person interview with the first author of the paper.
Specific labeling of synaptic schwann cells reveals unique cellular and molecular features
Castro, Ryan W.; Taetzsch, Thomas; Vaughan, Sydney K.; Godbe, Kerilyn; Chappell, John C.; Settlage, Robert E.; Valdez, Gregorio (2020-06-25)
Perisynaptic Schwann cells (PSCs) are specialized, non-myelinating, synaptic glia of the neuromuscular junction (NMJ), that participate in synapse development, function, maintenance, and repair. The study of PSCs has relied on an anatomy-based approach, as the identities of cell-specific PSC molecular markers have remained elusive. This limited approach has precluded our ability to isolate and genetically manipulate PSCs in a cell specific manner. We have identified neuron-glia antigen 2 (NG2) as a unique molecular marker of S100 beta+ PSCs in skeletal muscle. NG2 is expressed in Schwann cells already associated with the NMJ, indicating that it is a marker of differentiated PSCs. Using a newly generated transgenic mouse in which PSCs are specifically labeled, we show that PSCs have a unique molecular signature that includes genes known to play critical roles in PSCs and synapses. These findings will serve as a springboard for revealing drivers of PSC differentiation and function.

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