Accurate determination of the image pixel size is critical for quantitative cryo-electron microscopy analyses, yet existing calibration methods remain under-utilized because installation barriers and workflow complexity discourage routine adoption. To fill in this gap, a web-based application, WebCalEM, was developed to transform specialized calibration procedures into an accessible routine practice. Micrographs of any specimen with a known crystalline lattice, such as gold or graphene-oxide, are uploaded through a standard browser, processed entirely client-side, and analyzed with real-time visualization and downloadable statistical outputs. The application is delivered as a single self-contained HTML file that runs in any modern web browser without server-side computation, a configuration well suited to isolated core-facility microscope workstations. Cross-standard consistency between gold and graphene-oxide measurements across two microscopes and ten magnification settings yields a Bland-Altman bias of -0.005% of nominal with 95% limits of agreement of [-0.30%, +0.29%]. By delivering this workflow with no local installation, WebCalEM lowers the practical barrier to documented per-dataset magnification calibration in routine cryo-EM operation.
MOrbVis is an open-source web application that visualizes molecular orbitals directly in the browser without precomputed Gaussian Cube files. Reading only a Molden file, it evaluates Gaussian-type basis functions (s through g shells) on a three-dimensional grid through WebGPU compute shaders. Benchmarks on five devicesfrom a smartphone to a desktop with an NVIDIA RTX 5090show that single-orbital evaluation on grids exceeding 106 points finishes within 100 ms, up to 3 orders of magnitude faster than the single-threaded CPU path. The tool requires no installation and is available at https://yasuaki-ito.github.io/morbvis/.
The availability of touch-sensitive and haptic devices has been a keystone development for the inclusion of visually impaired people (VIPs) in modern, highly digitized work environments. Braille displays have proven efficient and versatile enough to parse large and complex text files, making bioinformatics and text-heavy programming accessible to VIPs. However, the complex graphical objects -combining numerous datasets- typically generated during data integration remain challenging, even with the aid of descriptive AI. This is particularly true in functional genomics. Here, we present VIJB, a simple application that displays the multilayered output of the JBROWSE genome browser on a Braille reader, enabling VIPs to fully participate in data integration in functional genomics. VIJB is programmed in Python and relies on the scientific library NumPy, the braillegraph and pyBigWig libraries, and the TABIX software. The architecture is summarized in Supplementary Material 1. VIJB is available for download at the GitHub repository https://GitHub.com/NiBuMNHN/VIJB and is licenced under the GPL 3.0. Supplementary data are available at Bioinformatics online.
Polygenic scores (PGSs) quantify individual genetic susceptibility to complex diseases and can identify high-risk individuals well before clinical onset. Their clinical translation, however, requires population-based reference resources, standardized benchmarking, and accessible tools for translating individual scores into disease likelihood. In this article, we systematically evaluate 3168 PGS models, primarily from the PGS Catalog, in 473,681 FinnGen participants, placing all models on a common performance scale to enable cross-model and cross-trait comparison. For each PGS, we create ancestry-adjusted reference distributions, providing a biobank-scale resource for interpreting individual scores. We perform phenome-wide association studies for each PGS, identifying 439,070 significant phenotypic associations, demonstratin g that integrating multiple scores improves predictive performance for most complex diseases, and providing public access to 11 top-performing interactive time-to-event models. All resources are accessible through the PGS Browser (pgs.nchigm.org), which offers a population-aware framework for score interpretation and lays groundwork for the clinical application of PGSs.
Lettuce (Lactuca sativa L.) is an economically important leafy vegetable within the Asteraceae family, cultivated worldwide across diverse agricultural systems. Recent advances in genomic and transcriptomic resources have positioned lettuce as a promising model system for functional genomics in the Asteraceae. However, currently available gene expression datasets lack comprehensive tissue-specific resolution, primarily focus on a single cultivar and are not visualised in an interpretable manner, limiting their utility for broader genetic and physiological studies. To bridge this gap, we developed the Lettuce Expression Browser (LEB), a publicly available platform providing high-resolution gene expression maps across various organs, tissues and developmental stages in both cultivated and wild lettuce species. The LEB integrates transcriptomic data from finely dissected seedlings, shoot tissues at various developmental stages and seedlings subjected to abiotic stresses (salt and far-red), visualised using the ggPlantmap R package. This platform offers an intuitive interface for exploring gene expression patterns and serves as a valuable resource for those studying lettuce development, stress responses and evolutionary genomics. The LEB is hosted on the LettuceKnow Web Portal (https://lettuce.bioinformatics.nl) and can be expanded to include additional datasets, enhancing its role as a key tool for lettuce research and crop improvement.
Cheminformatic analysis has been an active field for almost half a century, with considerable innovation accelerating drug discovery. However, the requirement for programming expertise prevents its popular use, often necessitating collaboration between multiple disciplines to integrate cheminformatics tasks into drug discovery pipelines. Various efforts have been made to mitigate this issue at the cost of cross-platform compatibility and preservation of data privacy. We introduce a static web application, QSAR, Quantitative Structure-Activity Relationship In The Browser (QITB), that performs various cheminformatic analyses on the user's device, with no external server required. It includes tools to access the publicly available ChEMBL database and tools for users to upload their own data. It automatically processes data, offers a range of interactive tools for data visualization and analysis, and supports the training and evaluation of lightweight machine-learning models. By being hosted on GitHub Pages, the QITB web app is broadly accessible and enables the use of cheminformatics by experts and nonexperts alike.
Spatial transcriptomics (ST) enables a high-resolution interrogation of molecular characteristics within specific spatial contexts and tissue morphology. Despite its potential, visualization of ST data is a challenging task due to the complexities in handling, sharing, and visualizing large image datasets together with molecular information. We introduce ScopeViewer, a browser-based software designed to overcome these challenges. ScopeViewer offers the following functionalities: (1) It visualizes large image data and associated annotations at various zoom levels, allowing for intricate exploration of the data; (2) It enables dual interactive viewing of the original images along with their annotations, providing a comprehensive understanding of the context; (3) It displays spatial molecular features with optimized bandwidth, ensuring a smooth user experience; and (4) It bolsters data security by circumventing data transfers. ScopeViewer offers the research community a convenient, powerful, and secure software for high-resolution images including pathology images and spatial transcriptomics. It serves as an open-source platform for imaging-based research. Future enhancements and new features will be shared on GitHub by the creators and are open for contributions from other researchers. ScopeViewer is freely available on the website at: https://cdc.biohpc.swmed.edu/scopeviewer.
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Prior authorization (PA) for exome or genome sequencing is a time-consuming process that impedes timely rare disease diagnosis. Large language model-based browser agents offer potential for automating these workflows, but their clinical reliability remain uncharacterized. We developed a sandbox compromising a simulated ES/GS PA submission payer portal and a synthetic EHR containing 836 patient records spanning compliant profiles and deficient profiles with different types of issues. Gemini 3 Pro, Gemini 3 Flash, and Claude Opus 4.5 were evaluated on task completion rate, form completion accuracy, and appropriate withholding for deficient profiles. Larger models achieved much higher task completion rates (Gemini 3 Pro 95.45%, Claude Opus 4.5 93.67%) compared to Gemini 3 Flash (56.05%), but nearly universally failed to withhold submission for deficient profiles whereas Gemini 3 Flash ironically demonstrated superior withholding performance (17.33%). In a non-agentic setting, Gemini 3 Pro correctly identified 91% of the issues in deficient profiles, indicating that withholding failure is attributable to the browser interaction rather than the model's reasoning limitations. Current LLM-based browser agents exhibit a systematic bias towards form submission that poses risks in PA workflows. A modular, multi-agent architecture with human supervision is necessary for a safe clinical deployment.
The aim of this article is to provide a conceptual description and clinical illustration of CHRONIC, a web-based multimodal program, by means of a didactically constructed clinical vignette. We present a clinically typical course of a 47-year-old woman with chronic pain disorder (F45.41), long-standing back and leg pain, pronounced avoidance and protective behavior, and marked restrictions in meaningful activities. CHRONIC is accessed via a browser and provides weekly unlocked video modules with in-session interactive exercises (auto-pause), worksheets, and structured home practice. Mindfulness exercises are provided as audio (up to ~15 minutes), and three physiotherapy units are embedded within the module flow (posture in daily life, dose-adaptable whole-body exercises, safe gait and stance). Brief weekly assessments (past 7 days) are displayed on the dashboard as line graphs of sum scores from selected MPI-D subscales. Written feedback is delivered in-app and via email. The vignette illustrates how psychoeducation (biopsychosocial model and vicious cycle of pain), acceptance and defusion strategies, and values-based goal setting can be translated into everyday action while gradually increasing pain-adapted physical activation. Over the 12-week course, the vignette illustrates a possible course toward personally meaningful goals with reduced avoidance and excessive guarding. This didactically constructed vignette illustrates the intended clinical application and conceptual structure of CHRONIC. The article is hypothesis-generating and does not allow conclusions regarding effectiveness, implementation success, or comparative utility in routine care. Ziel des Beitrags ist die konzeptionelle Beschreibung und klinische Illustration des webbasierten, multimodalen Programms CHRONIC anhand einer didaktisch konstruierten klinischen Vignette.Dargestellt wird der klinisch typische Verlauf einer 47-jährigen Patientin mit chronischer Schmerzstörung (F45.41) und langjährig persistierenden Rücken- und Beinschmerzen, ausgeprägtem Schon- und Vermeidungsverhalten sowie deutlicher Einschränkung alltagsrelevanter Aktivitäten. CHRONIC wird browserbasiert durchgeführt und umfasst wöchentlich freigeschaltete Videomodule mit automatisch pausierenden, interaktiven Übungen, Arbeitsblättern und verbindlicher Home-Practice. Ergänzend sind Achtsamkeitsübungen als Audio (bis ca. 15 Minuten) sowie drei in den Modulfluss integrierte physiotherapeutische Einheiten (Alltagshaltung, dosierbares Ganzkörper-Übungsprogramm, sicherer Gang und Stand) vorgesehen. Wöchentliche Kurzassessments (bezogen auf die vergangene Woche) werden im Dashboard als Kurvenverlauf von Summenscores ausgewählter MPI-D-Teilskalen visualisiert. Rückmeldungen erfolgen schriftlich in der Anwendung und per E-Mail.Die Vignette verdeutlicht, wie Psychoedukation (biopsychosoziales Modell, Teufelskreis des Schmerzes), Akzeptanz- und Defusionsstrategien sowie Wertearbeit und konkrete Commitments in einen handlungsorientierten Alltagstransfer überführt werden können, während parallel eine schmerzadaptierte körperliche Aktivierung aufgebaut wird. Die Illustration verdeutlicht eine schrittweise Annäherung an persönlich bedeutsame Ziele (z. B. Wiederaufnahme ausgewählter Aktivitäten) bei gleichzeitiger Reduktion von Vermeidung und übermäßigem Schonverhalten.Die dargestellte didaktisch konstruierte Vignette illustriert die klinische Anwendungslogik und den konzeptionellen Aufbau von CHRONIC. Der Beitrag ist hypothesengenerierend und erlaubt keine Aussagen zur Wirksamkeit, Versorgungseffektivität oder Implementierbarkeit im klinischen Alltag.
Currently, many global coral reef ecosystems are experiencing varying degrees of habitat degradation, raising the possibility of changes in the trophic structure of coral reef fish. Understanding how these trophic structures change over time is crucial for explaining the adaptive capacity of organisms under different environmental pressures. This study employed stable carbon and nitrogen isotope techniques to investigate the trophic dynamics of 21 species of parrotfish coexisting in the coral reef area of the Xisha Islands, South China Sea from 2018 to 2024. Under the combined pressures of coral reef habitat degradation and human activities, parrotfishes exhibited significant isotopic shifts over the seven-year study period. These shifts were reflected in a progressive increase in both nitrogen (δ15N) and carbon (δ13C) stable isotope values of the community, a pattern consistent with a potential change in assimilated dietary resources. Concurrently, the isotopic niche breadth of the community narrowed, indicating a pattern of dietary specialization toward a subset of available food resources, a trend that aligns with predictions from optimal foraging theory. Additionally, the overlap in trophic niches among different feeding functional groups (Scrapers, Excavators, and Browsers) increased, leading to higher dietary similarity. Parrotfish populations showed a decline in dietary diversity and trophic redundancy, whereas the stability of the trophic structure increased, especially within the Browser group. These findings enhance our understanding of the feeding adaptation strategies of coral reef fish in changing environments and provide an important foundation for future monitoring and conservation efforts of coral reef ecosystems. They are essential for maintaining the ecological functions of coral reef fish and the health of the ecosystem.
Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG-searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/ . The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas .
Plants available to wild herbivores, especially browsers, often contain plant secondary metabolites (PSMs). Herbivores have evolved behavioral, physiological, and microbial mechanisms for avoiding and detoxifying PSMs. The detoxification limitation hypothesis suggests that herbivores can reduce toxicity by consuming a mixture of PSMs to avoid overloading a particular detoxification pathway. Although this hypothesis has been examined for smaller mammalian hindgut-fermenters, less is known about responses to PSM mixtures in wild ruminants. To assess the role of host and microbial responses to PSM composition, we used controlled feeding trials to measure voluntary dry matter and PSM intake, urinary excretion of glucuronic acid (GA, a byproduct of PSM detoxification through conjugation), and the diversity and relative abundance of gastrointestinal bacterial families in the feces of two species of captive-raised deer (Odocoileus hemionus, O. virginianus). Deer were fed five mixtures of four purified PSMs that included two same-chemical class mixtures, two different-class mixtures, and one 4-way mixture of all chemicals. Overall, we found that PSM composition had minimal effect on intake, that GA was a consistent physiological biomarker of PSM intake regardless of PSM composition, and that dietary phenolics may influence microbial communities more than monoterpenes. Our results partially conformed to the detoxification limitation hypothesis, where deer consumed less of one same-class mixture (monoterpenes) than different-class mixtures. Our results point to the complexity of the interplay between different behavioral, physiological, and microbial mechanisms that can mediate the consequences of PSMs.
Phishing practice has radically changed as automation and artificial intelligence have taken new forms, enabling attackers to produce highly believable domain-spoofed content that is nearly indistinguishable from natural communication. Existing detection techniques, such as rule-based, blacklist-based, and single-modality approaches, tend to be weak, fail to generalise to unfamiliar attacks, and lack interpretability. Although the latest deep learning-driven solutions have improved detection performance, they remain vulnerable to adversarial attacks and provide fewer explanations for security analysts. To mitigate such challenges, the current paper outlines a neuro-symbolic multimodal phishing detection system that combines textual, visual, and metadata features and links them via a cross-attention-based fusion module. The framework improves the consistency of decisions in data-driven representations by incorporating explicit symbolic reasoning, leading to better decision-making, particularly when considering obfuscated and adversarial phishing patterns. The diffusion-based adversarial augmentation approach improves accuracy against phishing attacks using AI-generated similes. Conversely, continuous learning can be achieved in an online adaptation module through a replay buffer in response to a time-varying attack distribution. The SHAP-based explainability module provides explanations for features, making predictions interpretable and transparent. Many experiments across a variety of publicly available phishing datasets demonstrate that the suggested approach is effective, achieving a potential ROC-AUC of up to 97% on clean test data. The model is also more resilient to adversarial perturbations and achieves absolute AUC gains of 6-7% in cross-dataset generalisation compared to competitive baselines. The results are reported as the mean and standard deviation of repeated runs, and statistical significance (p < 0.05) is assessed to evaluate the reliability of the observed improvements. The suggested architecture provides a practical and reliable means of implementation, e.g., in security infrastructures such as email filters, web browsers, and enterprise threat intelligence systems, where robustness, generalisation, and interpretability are of utmost importance.
In the field of computer-generated holography (CGH), interference fringes are numerically calculated to reconstruct three-dimensional images. The point light source method, which requires the generation of 3D point cloud data, is widely adopted due to its computational simplicity. Previous studies by our group have explored various techniques for generating point clouds, including OpenGL- and Unity-based systems capable of producing photorealistic data. However, these systems required locally installed software, limiting accessibility. To overcome this limitation, we developed a WebGL-based application that enables users to generate point light sources directly through a web browser, without installation. The proposed system supports the generation of point cloud data from multiple viewpoints, which is essential for high-resolution and wide-viewing-angle CGH. This paper also presents verification results for two camera alignment methods and two depth measurement approaches, discussing their respective advantages and disadvantages.
Haplo2D6 is a free, browser-based tool that automates the translation of CYP2D6 genotype data into metabolizer phenotypes. Using haplotype reconstruction with the PHASE algorithm, integration of copy number variation estimates, and curated definitions from ClinPGx and PharmVar, Haplo2D6 assigns star alleles, incorporates gene deletions and duplications, calculates activity scores (AS), and predicts phenotype. This standardized, high-throughput approach improves reproducibility and reduces interpretation errors compared to manual workflows. It runs in any modern web browser, requires no installation, supports batch processing, and generates downloadable, human-readable results. Haplo2D6 is accessible at https://bioinfo.dcc.ufmg.br/Haplo2D6/ without registration.
Single-cell omics routinely profile millions of cells across the transcriptome and the epigenome. However, embeddings used for clustering, trajectory inference, and visualization remain unstable: stochastic variational autoencoders inject sampling noise at inference, and methods reported on idiosyncratic cohorts defeat head-to-head comparison. We introduce scCCVGBen, a benchmark of single-cell representation-learning methods. Its reference configuration is a centroid-coupled variational graph autoencoder built from three design choices: the centroid (deterministic posterior mean) used as the inference embedding, a coupling-regularized dual-reconstruction bottleneck, and a graph attention encoder over a k -nearest-neighbor cell-cell graph. We assess this configuration within a decoupled benchmark that varies the algorithmic core, encoder backbone, graph construction, dataset cohort, and evaluation suite as independent axes. The cohort, drawn from the Gene Expression Omnibus (GEO) and the European Nucleotide Archive (ENA), balances scRNA-seq and scATAC-seq equally and spans hematopoiesis, neuronal differentiation, immune populations, organ atlases, tumor microenvironments, and developmental time courses. Across the cohort, scCCVGBen improves average silhouette width by + 0.288 and intrinsic-overall geometry by + 0.233 over a stochastic variational encoder (VAE) on paired scRNA-seq; gains over scVI reach + 0.341 and + 0.331 , and on scATAC-seq, the gain over PeakVI on intrinsic geometry reaches + 0.346 . Robustness analyses across 14 graph encoders and 5 graph-construction strategies show where alternative architectures remain competitive. Three paired hematopoietic case studies: sleep-disrupted bone marrow alongside a gastric tumor atlas, cord blood megakaryopoiesis alongside aged hematopoietic stem cells, and radiation-injury hematopoiesis alongside the COVID-19 bronchoalveolar landscape, recover coherent latent-gene programs spanning hematopoietic, epithelial-stromal, megakaryocytic, and antiviral-macrophage axes. The benchmark cohort, per-method scores, and per-dataset metadata are released through three companion sites: a Hugo atlas, a Next.js interactive cohort browser, and a cross-tool discovery surface, so the cohort can be inspected without cloning the source repository. The result is a stable, interpretable embedding that carries cleanly from benchmarking to biological discovery.
Effective online communication is important for disseminating information during multi-jurisdictional enteric illness outbreaks in Canada. The Public Health Agency of Canada (PHAC) uses web-based Public Health Notices (PHNs) to communicate outbreak information and prevention measures. Despite this communication's importance, no study has examined online engagement with PHAC's PHNs. To assess access to and engagement with online information on multi-jurisdictional enteric illness outbreaks by analyzing website traffic and engagement metrics for PHAC's PHNs. Data on page and screen metrics, geographic location, device and browser types, and traffic source metrics for PHAC's PHN webpages (2020-2022) were obtained. Descriptive statistics were calculated for page and screen metrics data. Proportional frequencies were calculated for geographic location, device type, and traffic source metrics. Data were tabulated and visualized using R Studio. Public Health Notice webpages had an average of 2,729±16,685 page views and 2,490±15,201 visits; decreasing (but not significantly) over the study period. Average session duration was 165±124 seconds; increasing (but not significantly) over time. Most visits originated in Canada (89.0%±4.2%) and were from mobile devices (74.6%±3.3%). Traffic sources were primarily search (49.1%±13.0%), followed by direct (23.9%±6.7%), social media (21.2%±8.4%), and referral (5.7%±2.5%). The geographic location, device type, and traffic source changed significantly year by year. Engagement with PHAC's PHN webpages declined over the three years of the study, while mobile and search-driven access dominated and levels remained consistent over time. Social media generated comparatively little traffic. These findings suggest opportunities to enhance search optimization and social media amplification to improve outbreak communication.
Hierarchical quantitative profiles are widely used in microbiome studies and other domains. However, comparing multiple samples and experimental groups while preserving hierarchical structure remains challenging. Many existing workflows require extensive manual figure assembly or do not support aligned comparisons across conditions on a shared hierarchy. We developed MetaTree, an open-source platform that runs in a web browser for interactive visualization and comparative analysis of hierarchical quantitative data. MetaTree anchors samples, groups, and contrasts between groups to a shared reference hierarchy, preserving one-to-one node correspondence so that the same clade is compared in the same position across views. In addition to visualization, MetaTree integrates statistical testing for comparisons between two groups with false discovery rate (FDR) control, enabling users to identify clades with consistent differences between conditions and interpret them in hierarchical context. MetaTree also provides user configurable controls for visual encoding, filtering thresholds, label density, and layout, allowing figures to be adapted to different datasets and reporting needs. The interface remains usable for large hierarchies through interactive navigation, adaptive label handling, and branch collapsing. MetaTree is an installation-free web platform (https://byemaxx.github.io/MetaTree) for topology-consistent visualization and comparison of hierarchical profiles, supporting coordinated multi-panel exploration and automated comparison matrices to enable rapid generation of publication-ready figures for microbiome and other hierarchical datasets.
Hospital supply rooms are dense, vertically complex environments where clinicians may lose time locating items. Existing text-based inventory logs require mental translation from alphanumeric codes to physical space, adding cognitive load during time-sensitive tasks. Despite growing use of digital twins in health care, this technology has been underreported in supply room navigation. The objective of this study is to describe the design and feasibility of a browser-based three-dimensional (3D) digital twin system providing spatial guidance for locating supplies in a hospital clean supply room. A digital twin, defined here as a virtual interactive replica of a physical environment, was developed using React and Three.js to model a telemetry unit clean supply room. The system renders more than 100 storage bins using instanced rendering. Users search via a text interface; the system highlights the target bin and animates the camera to its position. The prototype achieved sub-10-ms search response times and loaded in under 1 second on standard hospital hardware. Two coresidents completed informal prototype walkthroughs over a 2-week period; these observations were anecdotal and were not part of a formal usability study. A 3D digital twin approach to supply room navigation is technically feasible using open-source web technologies at zero licensing cost and addresses spatial cognition challenges in dense health care storage environments. Formal usability evaluation is needed to quantify clinical effects.