Interactive Visualization Research Articles

Zebrafish (Danio rerio) as a Model System to Investigate the Role of the Innate Immune Response in Human Infectious Diseases

The zebrafish (Danio rerio) has emerged as a valuable model for studying host-pathogen interactions due to its unique combination of characteristics. These include extensive sequence and functional conservation with the human genome, optical transparency in larvae that allows for high-resolution visualization of host cell-microbe interactions, a fully sequenced and annotated genome, advanced forward and reverse genetic tools, and suitability for chemical screening studies. Despite anatomical differences with humans, the zebrafish model has proven instrumental in investigating immune responses and human infectious diseases. Notably, zebrafish larvae rely exclusively on innate immune responses during the early stages of development, as the adaptive immune system becomes fully functional only after 4–6 weeks post-fertilization. This window provides a unique opportunity to isolate and examine infection and inflammation mechanisms driven by the innate immune response without the confounding effects of adaptive immunity. In this review, we highlight the strengths and limitations of using zebrafish as a powerful vertebrate model to study innate immune responses in infectious diseases. We will particularly focus on host-pathogen interactions in human infections caused by various bacteria (Clostridioides difficile, Staphylococcus aureus, and Pseudomonas aeruginosa), viruses (herpes simplex virus 1, SARS-CoV-2), and fungi (Aspergillus fumigatus and Candida albicans).

The influence of visual and auditory environments in parks on visitors’ landscape preference, emotional state, and perceived restorativeness

Various auditory and visual factors influence people’s perception and restoration experiences in the spatial environments. However, few studies have treated these factors as a comprehensive system phenomenon to reveal their integrated effects. Therefore, a specific explanation of the primary pathways and factors that contribute to the main effects of park soundscapes and visual features and the resulting perceived restorativeness remains unclear. The study surveyed 861 visitors in five urban parks in China and collected audiovisual information. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the research explored the direct, indirect, and moderating effects of common audiovisual environments in parks on perceived restorativeness, emotional states, and preferences. The results indicate that most natural-related visual and auditory factors provide direct benefits for people’s perceived restorativeness, emotional state, and preference. Additionally, certain landscape features and types of sound sources, such as trees and water sounds, have indirect effects on activating restoration through preference and emotion mediation. The study also reveals the moderating effects of landscape features and sound source types on emotional and perceived restorativeness. Another noteworthy finding is the significant relationship between bird songs and the positive impact on perceived restorativeness, emotional state, and preference, which is closely related to acoustic quality indicators. These findings offer new insights for creating urban park spaces through visual and auditory interactions.

Fidaxomicin resistance in Clostridioides difficile: a systematic review and predictive modeling with RNA polymerase binding sites.

Fidaxomicin (FDX), an RNA polymerase (RNAP) inhibitor antibiotic, is a guideline-recommended therapy for Clostridioides difficile infection. Mutations associated with reduced FDX minimum inhibitory concentrations (MICs) have been identified. However, the molecular characterization of these mutations on FDX binding and the development of FDX resistance have not been studied. The purpose of this systematic review was to identify FDX resistance in C. difficile isolates and determine whether single nucleotide polymorphisms associated with increased FDX MIC aligned with the RNAP binding pocket interacting residues. A systematic literature search was done in PubMed (1991-2023) with identified articles and their bibliographies searched for papers that included C. difficile genetic mutations and increased FDX MIC. Visualization of FDX-RNAP interactions was performed on Schrödinger Maestro using the publicly available C. difficile RNAP with fidaxomicin sequence (code 7L7B) on the Protein Data Bank. Seven articles were identified after applying inclusion and exclusion criteria. The most common mutation in clinical and laboratory isolates was at position V1143 of the β subunit, which accounted for approximately 50% of the identified mutations. Most other mutations occurred within the β' subunit of RNAP. Approximately one-third of the identified mutation aligned directly with FDX interacting residues with C. difficile RNAP (7/20) with most of the remainder occurring within 5 Å of the binding residues. C. difficile strains with elevated FDX MIC align closely with the known RNAP binding residues. These data demonstrate the potential to identify genomic methods to identify emerging FDX resistance.

Emergence of Collective Behaviors for the Swarm Robotics Through Visual Attention-Based Selective Interaction

Emergence of Collective Behaviors for the Swarm Robotics Through Visual Attention-Based Selective Interaction

HBIM for conservation and valorization of structural heritage: The Stylite Tower at Umm ar-Rasas, Jordan

The Heritage Building Information Modeling (HBIM) is a consistent approach to support the multidisciplinary process of knowledge, conservation, and valorization of the historical building heritage, exploiting the combination of advanced 3D modelling and heterogeneous informative data. In the present paper, a highly customized HBIM workflow is developed for the enhancement and conservation of the byzantine Stylite Tower in the Jordan archaeological site of Umm ar-Rasas. The case study is considered a benchmark to test the effectiveness and the scalability of the proposed methodology for the broader set of ancient structures located in archaeological sites. The proposed HBIM process has a dual aim: the organization of heterogeneous and fragmented sources concerning the history and the actual state maintenance of the Tower and the development of a flexible tool to perform fast qualitative and quantitative analysis oriented towards conservation and management projects. The small scale of the structure and an innovative semi-automatic modelling process based on visual coding allowed for a stone-by-stone segmentation of the Tower. The model procedure is based on an information management workflow based on CIDOC-CRM ontology and the interchange format Industry Foundation Classes to ensure interoperability, developing an open-access interactive visualization of the model of the Tower, embedding organized document sources. The proposed HBIM model can also be a valuable tool for enhanced monument fruition and dissemination activities of the structure.

NcPlantDB: a plant ncRNA database with potential ncPEP information and cell type-specific interaction.

The field of plant non-coding RNAs (ncRNAs) has seen significant advancements in recent years, with many ncRNAs recognized as important regulators of gene expression during plant development and stress responses. Moreover, the coding potential of these ncRNAs, giving rise to ncRNA-encoded peptides (ncPEPs), has emerged as an essential area of study. However, existing plant ncRNA databases lack comprehensive information on ncRNA-encoded peptides (ncPEPs) and cell type-specific interactions. To address this gap, we present ncPlantDB (https://bis.zju.edu.cn/ncPlantDB), a comprehensive database integrating ncRNA and ncPEP data across 43 plant species. ncPlantDB encompasses 353 140 ncRNAs, 3799 ncPEPs and 4 647 071 interactions, sourced from established databases and literature mining. The database offers unique features including translational potential data, cell-specific interaction networks derived from single-cell RNA sequencing and Ribo-seq analyses, and interactive visualization tools. ncPlantDB provides a user-friendly interface for exploring ncRNA expression patterns at the single-cell level, facilitating the discovery of tissue-specific ncRNAs and potential ncPEPs. By integrating diverse data types and offering advanced analytical tools, ncPlantDB serves as a valuable resource for researchers investigating plant ncRNA functions, interactions, and their potential coding capacity. This database significantly enhances our understanding of plant ncRNA biology and opens new avenues for exploring the complex regulatory networks in plant genomics.

The knowledge layer: the role of key messages for translating data into meaning

Abstract The large volume of data generated by health information systems often remains siloed within the institutions that produce it, posing significant challenges to its reuse and interpretation. This fragmentation can result in conflicting information on critical health topics, complicating the decision-making process for policymakers. To address this issue, Belgium has initiated the ‘Health Status Report’ website, hosted at healthybelgium.be. This website aims to synthesize and present health data in a manner that supports evidence-based policy formulation. The website adopts a structured approach to data integration and interpretation: initially, we identify and prioritize key health topics based on their relevance and the quality of available data. Subsequently, we merge and analyze data from diverse sources to discern patterns and trends that are crucial for public health monitoring. The insights gained are then presented through both narrative texts and interactive visualizations, facilitating access and understanding for a broad audience. Crucial to this process is ongoing communication with experts and stakeholders, ensuring that the data is not only accurately interpreted but also aligns with the needs and expectations of its users. We also aim to translate the raw data into meaningful key messages by consulting with internal and external experts. This interactive platform thus serves as a critical tool for translating complex health data into actionable knowledge, enabling informed public health strategies and interventions.

Microsatellites explorer: A database of short tandem repeats across genomes

Short tandem repeats (STRs) are widespread, repetitive elements, with a number of biological functions and are among the most rapidly mutating regions in the genome. Their distribution varies significantly between taxonomic groups in the tree of life and are highly polymorphic within the human population. Advances in sequencing technologies coupled with decreasing costs have enabled the generation of an ever-growing number of complete genomes. Additionally, the arrival of accurate long reads has facilitated the generation of Telomere-to-Telomere (T2T) assemblies of complete genomes. Nevertheless, there is no comprehensive database that encompasses the STRs found per genome across different organisms and for different human genomes across diverse ancestries. Here we introduce Microsatellites Explorer, a database of STRs found in the genomes of 117,253 organisms across all major taxonomic groups, 15 T2T genome assemblies of different organisms, and 94 human haplotypes from the human pangenome. The database currently hosts 406,758,798 STR sequences, serving as a centralized user-friendly repository to perform searches, interactive visualizations, and download existing STR data for independent analysis. Microsatellites Explorer is implemented as a web-portal for browsing, analyzing and downloading STR data. Microsatellites Explorer is publicly available at https://www.microsatellitesexplorer.com.

Rapid QC-MS: Interactive Dashboard for Synchronous Mass Spectrometry Data Acquisition Quality Control.

Consistently collecting high-quality liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) data is a time-consuming hurdle for untargeted workflows. Analytical controls such as internal and biological standards are commonly included in high-throughput workflows, helping researchers recognize low-integrity specimens regardless of their biological source. However, evaluating these standards as data are collected has remained a considerable bottleneck─in both person-hours and accuracy. Here we present Rapid QC-MS, an automated, interactive dashboard for assessing LC-MS/MS data quality. Minutes after a new data file is written, a browser-viewable dashboard is updated with quality control results spanning multiple performance dimensions such as instrument sensitivity, in-run retention time shifts, and mass accuracy drift. Rapid QC-MS provides interactive visualizations that help users recognize acute deviations in these performance metrics, as well as gradual drifts over periods of hours, days, months, or years. Rapid QC-MS is open-source, simple to install, and highly configurable. By integrating open-source Python libraries and widely used MS analysis software, it can adapt to any LC-MS/MS workflow. Rapid QC-MS runs locally and offers optional remote quality control by syncing with Google Drive. Furthermore, Rapid QC-MS can operate in a semiautonomous fashion, alerting users to specimens with potentially poor analytical integrity via frequently used messaging applications. Initially developed for integration with Thermo Orbitrap workflows, Rapid QC-MS offers a fast, straightforward approach to help users collect high-quality untargeted LC-MS/MS data by eliminating many of the most time-consuming steps in manual data curation. Download for free: https://github.com/czbiohub-sf/Rapid-QC-MS.

Mining User Reviews for Key Design Features in Cognitive Behavioral Therapy-Based Mobile Mental Health Apps.

Background: Cognitive behavioral therapy (CBT)-based mobile apps have been shown to improve CBT-based interventions effectiveness. Despite the proliferation of these apps, user-centered guidelines pertaining to their design remain limited. The study aims to identify design features of CBT-based apps using online app reviews. Methods: We used 4- and 5-star reviews, preprocessed the reviews, and represented the reviews using word-level bigrams. Then, we leveraged latent Dirichlet allocation (LDA) and visualization techniques using python library for interactive topic model visualization to analyze the review and identify design features that contribute to the success and effectiveness of the app. Results: A total of 24,902 reviews were analyzed. LDA optimization resulted in 86 topics that were labeled by two independent researchers, with an interrater Cohen's kappa value of 0.86. The labeling and grouping process resulted in a total of six main design features for effective CBT-based mobile apps, namely, mental health management and support, credibility support, self-understanding and personality insights, therapeutic approaches and tools, beneficial rescue sessions, and personal growth and development. Conclusions: The high-level design features identified in this study could evidently serve as the backbone of successful CBT-based mobile apps for mental health.

TIBA: A web application for the visual analysis of temporal occurrences, interactions, and transitions of animal behavior.

Data in behavioral research is often quantified with event-logging software, generating large data sets containing detailed information about subjects, recipients, and the duration of behaviors. Exploring and analyzing such large data sets can be challenging without tools to visualize behavioral interactions between individuals or transitions between behavioral states, yet software that can adequately visualize complex behavioral data sets is rare. TIBA (The Interactive Behavior Analyzer) is a web application for behavioral data visualization, which provides a series of interactive visualizations, including the temporal occurrences of behavioral events, the number and direction of interactions between individuals, the behavioral transitions and their respective transitional frequencies, as well as the visual and algorithmic comparison of the latter across data sets. It can therefore be applied to visualize behavior across individuals, species, or contexts. Several filtering options (selection of behaviors and individuals) together with options to set node and edge properties (in the network drawings) allow for interactive customization of the output drawings, which can also be downloaded afterwards. TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. The web application and usage instructions are available at tiba.inf.uni-konstanz.de. The source code is publicly available on GitHub: github.com/LSI-UniKonstanz/tiba.

Abietic acid antagonizes the anti-inflammatory effects of celecoxib and ketoprofen: Preclinical assessment and molecular dynamic simulations

The present work is designed to explore the anti-inflammatory properties of AA and its modulatory effects on celecoxib (CEL) and ketoprofen (KET) through in vitro, ex vivo, in vivo, and in silico approaches. Different concentrations of AA were utilized to evaluate the membrane-stabilizing potential via egg albumin and the Human Red Blood Cell (HRBC) denaturation model. In the animal model, formalin (50 μL) was injected into the right hind paw of young chicks to induce inflammation. AA was administered at 20 and 40 mg/kg (p.o.) to the experimental animals. We used CEL and KET as positive controls. The vehicle was provided as a control group. Two combinations of AA with CEL and KET were also investigated in all tests to assess the modulatory activity of AA. In addition, in silico investigation was used for predictions about drug-likeness, pharmacokinetics, and toxicity of the selected chemical compounds, and the study also evaluated the binding affinity, visualization, and stability of ligand-receptor interactions through molecular dynamic (MD) simulation. Results manifested that AA concentration-dependently significantly inhibited the egg albumin denaturation (IC50: 27.53 ± 0.88 μg/ml) and breakdown of HRBC (IC50: 15.69 ± 0.75 μg/ml), indicating the membrane stabilizing potential compared to the control group. AA also significantly (p < 0.05) lessened the frequency of licking and alleviated the paw edema in a dose-dependent manner in an in vivo test. However, AA reduced the activity of CEL and KET in combination treatment. AA showed good pharmacokinetic characteristics to be considered as a therapeutic candidate. Additionally, the in silico study displayed that AA demonstrated a relatively higher docking score of −9.1 kcal/mol with the cyclooxygenase-2 (COX-2) enzyme and stable binding in MD simulation. Whereas the standard ligand (CEL) expressed the highest binding value of −9.2 kcal/mol to the COX-2.

Single-Molecule Kinetic Observation of Antibody Interactions with Growing Amyloid β Fibrils.

Understanding the dynamic assembly process of amyloid β (Aβ) during fibril formation is essential for developing effective therapeutic strategies against Alzheimer's disease. Here, we employed high-speed atomic force microscopy to observe the growth of Aβ fibrils at the single-molecule level, focusing specifically on their interaction with anti-Aβ antibodies. Our findings show that fibril growth consists of intermittent periods of elongation and pausing, which are dictated by the alternating addition of Aβ monomers to protofilaments. We highlight the distinctive interaction of antibody 4396C, which specifically binds to the fibril ends in the paused state, suggesting a unique mechanism to hinder fibril elongation. Through real-time visualization of fibril growth and antibody interactions combined with molecular simulation, this study provides a refined understanding of Aβ assembly during fibril formation and suggests novel strategies for Alzheimer's therapy aimed at inhibiting the fibril elongation.

PlasmidScope: a comprehensive plasmid database with rich annotations and online analytical tools.

Plasmids are extrachromosomal genetic molecules that replicate independent of chromosomes in bacteria, archaea, and eukaryotic organisms. They contain diverse functional elements and are capable of horizontal gene transfer among hosts. While existing plasmid databases have archived plasmid sequences isolated from individual microorganisms or natural environments, there is a need for a comprehensive, standardized, and annotated plasmid database to address the vast accumulation of plasmid sequences. Here, we propose PlasmidScope (https://plasmid.deepomics.org/), a plasmid database offering comprehensive annotations, automated online analysis, and interactive visualization. PlasmidScope harbors a substantial collection of 852 600 plasmids curated from 10 repositories. Along with consolidated background information, PlasmidScope utilizes 12 state-of-the-art tools and provides comprehensive annotations for the curated plasmids, covering genome completeness, topological structure, mobility, host source, tRNA, tmRNA, signal peptides, transmembrane proteins and CRISPR/Cas systems. PlasmidScope offers diverse functional annotations for its 25 231 059 predicted genes from 9 databases as well as corresponding protein structures predicted by ESMFold. In addition, PlasmidScope integrates online analytical modules and interactive visualization, empowering researchers to delve into the complexities of plasmids.

Integration of Digital Repositories and Spatial Design within the Metaverse: the Evaluation of Features and Narratives to set Learning Environments on Cultural Heritage

Abstract. The Metaverse is rapidly advancing across cultural, professional, and service sectors, enhancing data compatibility and interaction. Its architectural design supports both visual interaction and information layers, characterising an ideal platform for the promotion of Digital Heritage. The digitisation of Cultural Heritage and the creation of Digital Repositories find complementarity in the Metaverse, which enables social interactions between Digital Heritage contents and virtual communities. This integration is pivotal for developing Learning Environments, where accessible virtual products can be combined with original digital storytelling and narratives.The paper presents methods and results from an Erasmus+ international school, which focused on using digital communication and 3D modelling tools to create immersive narratives on Mediterranean architectural modernity. Students from various Cultural Heritage disciplines designed virtual exhibitions within the Metaverse platform Spatial and open repository materials. The research concentrated on the application of Metaverse platforms for their spatial design and educational utility within the Heritage sector. The activities included developing digital narratives and interactive exhibitions enriched with multimedia data from digital repositories. The study discusses the limitations of customising visual materials, the importance of repository connections, user experience design, and the potential for future developments in Metaverse applications for Cultural Heritage learning environments and storytelling.

Deep learning-powered efficient characterization and quantification of microplastics

Characterizing and quantifying microplastics (MPs) are time-consuming and labor-intensive tasks traditionally. This paper presents an artificial intelligence (AI) framework aiming to automate these tasks by integrating computer vision and deep learning techniques. The approach leverages Fourier Transform Infrared (FTIR) spectra and visual images. Primary novelties of this research involve the development of: (1) an AI framework integrating efforts of data processing, analytics, visualization, and human-computer interaction; (2) a method for transforming FTIR data into contour images; (3) data augmentation strategies for resolving data scarcity and imbalance issues; (4) deep learning models for identifying MPs; (5) computer vision algorithms for quantifying MPs; and (6) an engineer-friendly graphic user interface (GUI) for enhancing data accessibility. The AI framework has been applied to polyethylene, polypropylene, polystyrene, polyamide, ethylene-vinyl acetate, and cellulose acetate. Results confirmed the efficacy of the framework, exhibiting high accuracy scores in classification (98 %), segmentation (99 %), and quantification (96 %) tasks. This research advances the capability of automatic assessment of MPs.

Research on the Interactive Effects of Parenting Advertising Under the Sustainable Development Goals (SDGS)

Objective: The objective of this study is to investigate the different effects of advertising interactive experiences, and explore effective advertising interactive methods, to provide effective parenting advertising training for abusive parents. Theoretical Framework: Refers to the multi-sensory advertising interaction model based on the studies before, such as the AIEDA tourism advertising effects model, schema congruence theory, and a spiral brand experience concept. Method: This study conducted the distinct "Systematic Literature Review Synthesis Process", a stand-alone literature review typology that helps make sense of a chosen body of current literature and helps determine the theoretical framework at the early stages of research ideation. Results and Discussion: The results revealed that visual, auditory, and multi-sensory interactions all have different elements and characteristics and could cause different levels of attention, memory, and emotions for audiences. Research Implications: The results are expected to guide the development of a theoretical framework for combining advertising and user experience interaction. Originality/Value: The research helps to identify interactive sensory experience characteristics in advertisements, guide the effective dissemination of parenting public service advertisements, and create a happier family atmosphere for children, to promote SDG 3 on ensuring healthy lifestyles and promoting the well-being of people of all ages.

Reflections on interactive visualization of electronic health records: past, present, future.

Reflections on interactive visualization of electronic health records: past, present, future.

Research on Spatial Data Aggregation Based on Aggregation Degree Function

Abstract. Restricted by the development level of hardware and software technology, computers cannot load massive data at one time, coupled with the fact that the three-dimensional linear scene is characterized by complicated lines, irregular shapes of features and a large number of features. Therefore, it is necessary to seek a three-dimensional spatial data organization and scheduling method applicable to the railroad scene to realize the display and interaction of the scene. In this paper, we propose a data organization method based on the aggregation degree function for the 3D model of features. The feature model is projected to generate an orthographic projection map, the cluster division rule is designed to divide the subsets, the feature model after clustering is aggregated using the feature model aggregation rule, and the aggregated model is displayed according to the aggregation degree function and viewpoint factor. The results of the test applied to the railroad scene show that the 3D spatial data aggregation based on the aggregation degree function can improve the loading speed of the 3D scene, and can effectively support the application of interactive visualization of the railroad 3D scene.

Near Real-Time Responsive Flood Event Representation: An Open-Source Interactive Web Application Architecture

Abstract. The adoption of accessible Digital Twin technology in flood applications has been impeded by a notable lack of practical examples. Arguably, the most distinguishing feature of Digital Twin technology is the integration of near real-time data analytics through IoT sensor connectivity, which has remained underutilised in flood applications and therefore indicates a critical research gap. This project endeavoured to develop a comprehensive and replicable open-source architecture framework, specifically tailored for near real-time responsive flood event representation. The resultant interactive web application integrated near real-time river height and rain fall data streams and performed on-demand data analytics. Key results include the establishment of a back-end spatial database, a coupled physical city and digital space model, and a functional holistic front-end user interface. Additionally, this research aligned with the Gemini Principles by emphasising data interoperability and maintaining an information feedback loop. The study also aimed to configure near real-time IoT sensor connections, implement event triggers, and deliver interactive visualisations in an easily accessible format. The research addressed key questions surrounding the effective integration of IoT sensor data, identification of crucial flood indicators and parameters, and rapid quantification of flood event impacts. Ultimately, this research project demonstrates how Digital Twin technology can swiftly provide decision-makers with crucial insights during flood disaster events.