Interactive Web Research Articles

MiR‑155 promotes an inflammatory response in HaCaT cells via the IRF2BP2/KLF2/NF‑κB pathway in psoriasis.

Psoriasis is a chronic inflammatory skin condition with numerous causes, including genetic, immunological and infectious factors. The course of psoriasis is long and recurrence is common; pathogenesis is not completely understood. However, there is an association between advancement of psoriasis and aberrant microRNA (miR or miRNA)‑155 expression. Through bioinformatics, the present study aimed to analyze the differentially expressed genes and miRNAs in psoriasis and its biological mechanism and function psoriatic inflammation. First of all, differentially expressed genes (DEGs) and miRNAs (DEMs) in patients with psoriasis were identified using GEO2R interactive web application. A psoriasis inflammatory model was established using lipopolysaccharide (LPS)‑treated HaCaT keratinocytes, which were transfected with miR‑155 mimic or inhibitor. Cell Counting Kit‑8 was used for the assessment of cell viability and proliferation, and changes in the cell cycle were examined using flow cytometry. ELISA and reverse transcription‑quantitative PCR (RT‑qPCR) were used to detect the expression levels of the inflammatory factors IL‑1β and IL‑6. The dual‑luciferase reporter assay was used to verify the targeting association between miR‑155‑5p and IFN regulatory factor 2 binding protein 2 (IRF2BP2). To verify the targeting association of miR‑155 and the IRF2BP2/kruppel‑like factor 2 (KLF2)/NF‑κB signaling pathway, expression levels of IRF2BP2, KLF2 and p65 were identified by RT‑qPCR and western blotting. IRF2BP2 levels were also confirmed by immunofluorescence, in conjunction with bioinformatics database analysis. Overexpression of miR‑155 inhibited proliferation of HaCaT cells and increased the number of cells in S phase and decreasing number of cells in G1 and G2 phase. In the LPS‑induced inflammatory state, miR‑155 overexpression heightened the inflammatory response of HaCaT cells while inhibition of miR‑155 lessened it. Suppression of inflammatory cytokine expression by miR‑155‑5p inhibitor was reversed by knockdown of IRF2BP2. miR‑155 was shown to interact with IRF2BP2 to negatively regulate its expression, leading to decreased KLF2 expression and increased p65 expression and secretion of inflammatory factors, intensifying the inflammatory response of HaCaT cells. Therefore, miR‑155 may contribute to development of psoriasis by inducing tissue and cell damage by increasing the inflammatory response of HaCaT cells via the IRF2BP2/KLF2/NF‑κB pathway. In conclusion, the results of the present study offer novel perspectives on the role of miR‑155 in the onset and progression of psoriasis.

One Health in Europe: from concept to practice

Abstract The One Health concept is a comprehensive approach that highlights the interconnectedness of human, animal, and environmental health. Understanding these interrelationships is essential for effectively managing and mitigating emerging health threats. This approach emphasizes that health issues arise from a complex web of interactions involving humans, animals, and ecosystems. Emerging health threats, such as zoonotic diseases (e.g., mpox, Ebola, avian influenza), antibiotic resistance, and environmental degradation, pose significant risks to global health. Zoonotic diseases, which are transmitted between animals and humans, highlight the direct links between animal and human health. The increase in antibiotic resistance, driven by overuse in both human medicine and livestock farming, leads to the rise of resistant pathogens. Environmental issues like climate change, deforestation, and pollution further exacerbate these threats by altering habitats, disrupting ecosystems, and affecting disease vectors. Addressing these interconnected challenges requires a unified approach that integrates human, animal, and environmental considerations. For example, climate change can shift the distribution of disease vectors like mosquitoes, leading to the spread of diseases such as malaria and dengue fever. Likewise, deforestation can heighten the risk of zoonotic spillover by bringing humans into closer contact with wildlife. 1. To tackle these complex challenges, several measures are crucial: • Integrated surveillance systems Developing systems that monitor human, animal, and environmental health data collectively can improve early detection of outbreaks. Sharing information across sectors is a prerequisite for effective identification of emerging threats. • Strengthening veterinary and public health collaboration Joint research, surveillance, and outbreak management efforts can lead to a more coordinated approach to health emergencies. • Promoting One Health education and training Educating professionals in various fields fosters a collaborative approach to health issues. Training programmes can build a shared understanding of health interconnections. • Implementing sustainable environmental practices Adopting sustainable practices to address environmental degradation helps reduce risks associated with habitat destruction and pollution. • International collaboration and agreements facilitate resource sharing, information exchange, and best practices. 2. To enhance public health strategies within the One Health framework: • Enhance interdisciplinary research Promote research on the intersections of human, animal, and environmental health to understand how changes in one area affect others and to develop more effective interventions. • Foster community engagement Engage communities to improve the adoption of preventive measures and build resilience against health threats through public awareness and community-based programs. Leverage technology and innovation Innovations can offer valuable insights such as data analytics, remote sensing, and genomic surveillance. In our upcoming plenary session, experts from veterinary and public health sciences will present practical examples on One Health collaboration in Europe and discuss how to address challenges in implementing the approach. Moderator Ricardo Mexia Chair of the 17th EPH Conference 2024, President EUPHA Infectious diseases control section Keynote speaker Lorena Boix Deputy Director-General, Directorate General for Health and Food Safety (DG SANTE), European Commission Speakers/Panellists Stef Bronzwaer Cross-Agency One Health Task Force, European Food Safety Authority (EFSA) Barbara Häsler Royal Veterinary College, UK Susana Guedes Pombo Chief Veterinary Officer, Portugal, President World Organization for Animal Health (WOAH) Eva Zažímalová Member of European Commission's Group of Chief Scientific Advisors, Professor of Plant Anatomy and Physiology, Charles University, Czech Republic

Collapsible tree: interactive web app to present collapsible hierarchies.

A crucial component of intuitive data visualization is presenting a hierarchical tree structure with interactive functions. For example, single-cell transcriptomics studies may generate gene expression values with developmental trajectories or cell lineage structures. Two common visualization methods, t-SNE and UMAP, require two separate figures to depict the distribution of cell types and gene expression data, with low-dimension projections that may not capture the hierarchical structures among cells. Here, we present a JavaScript framework and an interactive web app named Collapsible Tree, which presents values jointly with interactive, expandable, and collapsible lineage structures. For example, the Collapsible Tree presents cellular states and gene expression from single-cell transcriptomics within a single hierarchical plot, enabling comparisons of gene expression across lineages and subtle patterns between sub-lineages. Our framework can facilitate the exploration of complicated value patterns that are not evident in UMAP or t-SNE plots. The Collapsible Tree web interface is available at https://collapsibletree.data2in.net. The JavaScript library source code is available at https://github.com/data2intelligence/collapsible_tree.

Ant‐Pollination: Conditional Outcomes Depending on Environmental Features and Species Interactions

ABSTRACTThe intricate web of interactions in nature has led to unexpected partnerships between plants and animals, greatly influencing ecosystem dynamics. In this discussion, we'll explore the Pollination Syndrome Hypothesis and consider a scenario where a partnership with unexpected pollinators emerges. We suggest that ant pollination has been largely overlooked, but ants can surprisingly play a crucial role and have a history of success in pollinating dry system plants. We will present both negative and positive aspects that must be observed in ant‐pollination syndrome. Additionally, we aim to explore the often‐underestimated phenomenon of ant pollination and the overlooked tiny, discreet, unnoticed flowers found in our fields and forests, especially in dry ecosystems, savannas and mountain fields, which may hold numerous undiscovered secrets about these interactions. We encourage young biologists to engage in natural history observations and to perform manipulative experiments directly in the field to understand the true nature of these successful ant‐pollinations.

Dynamics of ecosystem services along ecological network seascapes

Abstract Human societies depend on services provided by ecosystems, from local needs such as clean water and pest control to global services like the ozone layer and the ocean biological pump. Ecosystem services are linked to the states of the ecosystem, which are, in turn, governed by a web of ecological interactions. These interactions, along with the services they support, are under threat from environmental changes driven by human activities. Therefore, safeguarding these vital services requires an understanding of how the structure and dynamics of ecological interactions are affected by environmental change. A critical step towards this goal is the development of a theoretical framework that can elucidate how ecosystem services are sustained or impaired by interactions within ecosystems in fluctuating environments. Recent years have seen progress in characterizing the organization and dynamics of ecological networks. However, linking temporally varying network structure in fluctuating environments, the seascapes of ecological networks, and their impact on services remains a challenge. We propose an approach based on merging ecological network analysis with Boolean functions and modeling of fluctuating environments to address how services are affected by environmental change. We review aspects of Boolean Network models and illustrate the approach using biologically inspired Boolean rules that involve predator-prey cycles, trophic cascades, and mutualisms formed by plants and their frugivores. This approach aims to contribute to the study of how the organization of ecological interactions affects the persistence of ecosystem services. Specifically, we discuss how this approach can provide new insights into how environmental change affects the relationship between ecological networks and ecosystem services. The combination of information on the natural history of species interactions and ecosystem services, Boolean networks, and models for fluctuating environments may contribute to conservation strategies for preserving biodiversity and ecosystem services in the face of ongoing environmental change.

Multifaceted effects of variable biotic interactions on population stability in complex interaction webs

Recent studies have revealed that biotic interactions in ecological communities vary over time, possibly mediating community responses to anthropogenic disturbances. This study investigated the heterogeneity of such variability within a real community and its impact on population stability in the face of pesticide application, particularly focusing on density-dependence of the interaction effect. Using outdoor mesocosms with a freshwater community, we found considerable heterogeneity in density-dependent interaction variability among links in the same community. This variability mediated the stability of recipient populations, with negative density-dependent interaction variability stabilizing whereas positive density-dependence and density-independent interaction variability destabilizing populations. Unexpectedly, the mean interaction strength, which is typically considered crucial for stability, had no significant effect, suggesting that how organisms interact on average is insufficient to predict the ecological impacts of pesticides. Our findings emphasize the multifaceted role of interaction variability in predicting the ecological consequences of anthropogenic disturbances such as pesticide application.

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.

Stabilizing selection and adaptation shape cis and trans gene expression variation in C. elegans.

An outstanding question in the evolution of gene expression is the relative influence of neutral processes versus natural selection, including adaptive change driven by directional selection as well as stabilizing selection, which may include compensatory dynamics. These forces shape patterns of gene expression variation within and between species, including the regulatory mechanisms governing expression in cis and trans . In this study, we interrogate intraspecific gene expression variation among seven wild C. elegans strains, with varying degrees of genomic divergence from the reference strain N2, leveraging this system's unique advantages to comprehensively evaluate gene expression evolution. By capturing allele-specific and between-strain changes in expression, we characterize the regulatory architecture and inheritance mode of gene expression variation within C. elegans and assess their relationship to nucleotide diversity, genome evolutionary history, gene essentiality, and other biological factors. We conclude that stabilizing selection is a dominant influence in maintaining expression phenotypes within the species, and the discovery that genes with higher overall expression tend to exhibit fewer expression differences supports this conclusion, as do widespread instances of cis differences compensated in trans . Moreover, analyses of human expression data replicate our finding that higher expression genes have less variable expression. We also observe evidence for directional selection driving expression divergence, and that expression divergence accelerates with increasing genomic divergence. To provide community access to the data from this first analysis of allele-specific expression in C. elegans , we introduce an interactive web application, where users can submit gene-specific queries to view expression, regulatory pattern, inheritance mode, and other information: https://wildworm.biosci.gatech.edu/ase/ .

PhenoMultiOmics: an enzymatic reaction inferred multi-omics network visualization web server.

Enzymatic reactions play a pivotal role in regulating cellular processes with a high degree of specificity to biological functions. When enzymatic reactions are disrupted by gene, protein, or metabolite dysfunctions in diseases, it becomes crucial to visualize the resulting perturbed enzymatic reaction-induced multi-omics network. Multi-omics network visualization aids in gaining a comprehensive understanding of the functionality and regulatory mechanisms within biological systems. In this study, we designed PhenoMultiOmics, an enzymatic reaction-based multi-omics web server designed to explore the scope of the multi-omics network across various cancer types. We first curated the PhenoMultiOmics Database (PMODB), which enables the retrieval of cancer-gene-protein-metabolite relationships based on the enzymatic reactions. We then developed the MultiOmics network visualization module to depict the interplay between genes, proteins, and metabolites in response to specific cancer-related enzymatic reactions. The biomarker discovery module facilitates functional analysis through differential omic feature expression and pathway enrichment analysis. PhenoMultiOmics has been applied to analyze transcriptomics data of gastric cancer and metabolomics data of lung cancer, providing insights into interrupted enzymatic reactions and the associated multi-omics network. PhenoMultiOmics is freely accessed at https://phenomultiomics.shinyapps.io/cancer/ with a user-friendly and interactive web interface. Supplementary data are available at Bioinformatics online.

Leveraging Transfer Learning for Predicting Protein-Small Molecule Interactions.

A complex web of intermolecular interactions defines and regulates biological processes. Understanding this web has been particularly challenging because of the sheer number of actors in biological systems: ∼10 4 proteins in a typical human cell offer a plausible 10 8 interactions. This number grows rapidly if we consider metabolites, drugs, nutrients, and other biological molecules. The relative strength of interactions also critically affects these biological processes. However, the small and often incomplete datasets (10 3 -10 4 protein-ligand interactions) traditionally used for binding affinity predictions limit the ability to capture the full complexity of these interactions. To overcome this challenge, we developed Yuel 2, a novel neural network-based approach that leverages transfer learning to address the limitations of small datasets. Yuel 2 is pre-trained on a large-scale dataset to learn intricate structural features and then fine-tuned on specialized datasets like PDBbind to enhance the predictive accuracy and robustness. We show that Yuel 2 predicts multiple binding affinity metrics - Kd, Ki, and IC50 - between proteins and small molecules, offering a comprehensive representation of molecular interactions crucial for drug design and development.

CTPAD: an interactive web application for comprehensive transcriptomic profiling in allergic diseases

BackgroundAllergic diseases are systemic chronic inflammatory diseases associated with multiorgan damage and complex pathogenesis. Several studies have revealed the association of gene expression abnormalities with the development of allergic diseases, but the biomedical field still lacks a public platform for comprehensive analysis and visualization of transcriptomic data of allergic diseases.ObjectiveThe aim of the study is to provide a comprehensive web tool for multiple analysis in allergic diseases.MethodsWe retrieved and downloaded human and mouse gene expression profile data associated with allergic diseases from the Gene Expression Omnibus (GEO) database and standardized the data uniformly. We used gene sets obtained from the MSigDB database for pathway enrichment analysis and multiple immune infiltration algorithms for the estimation of immune cell proportion. The basic construction of the web pages was based on the Shiny framework. Additionally, more convenient features were added to the server to improve the efficiency of the web pages, such as jQuery plugins and a comment box to collect user feedback.ResultsWe developed CTPAD, an interactive R Shiny application that integrates public databases and multiple algorithms to explore allergic disease-related datasets and implement rich transcriptomic visualization capabilities, including gene expression analysis, pathway enrichment analysis, immune infiltration analysis, correlation analysis, and single-cell RNA sequencing analysis. All functional modules offer customization options and can be downloaded in PDF format with high-resolution images.ConclusionsCTPAD largely facilitates the work of researchers without bioinformatics background to enable them to better explore the transcriptomic features associated with allergic diseases. CTPAD is available at https://smuonco.shinyapps.io/CTPAD/.

StopKB: a comprehensive knowledgebase for nonsense suppression therapies.

Nonsense variations, characterized by premature termination codons, play a major role in human genetic diseases as well as in cancer susceptibility. Despite their high prevalence, effective therapeutic strategies targeting premature termination codons remain a challenge. To understand and explore the intricate mechanisms involved, we developed StopKB, a comprehensive knowledgebase aggregating data from multiple sources on nonsense variations, associated genes, diseases, and phenotypes. StopKB identifies 637 317 unique nonsense variations, distributed across 18 022 human genes and linked to 3206 diseases and 7765 phenotypes. Notably, ∼32% of these variations are classified as nonsense-mediated mRNA decay-insensitive, potentially representing suitable targets for nonsense suppression therapies. We also provide an interactive web interface to facilitate efficient and intuitive data exploration, enabling researchers and clinicians to navigate the complex landscape of nonsense variations. StopKB represents a valuable resource for advancing research in precision medicine and more specifically, the development of targeted therapeutic interventions for genetic diseases associated with nonsense variations. Database URL: https://lbgi.fr/stopkb/.

The “Cognitive” Architectural Design Process and Its Problem with Recent Artificial Intelligence Applications

The connection between cognitive science and the architectural design process reveals significant gaps that limit the full potential of creating effective built environments. A key issue is the insufficient integration of cognitive principles into design workflows. Architects frequently rely on traditional methods and aesthetic considerations without fully understanding how spatial configurations influence human cognition and behavior. While recent AI applications in architecture, such as Computer-Aided Drafting (CAD), Building Information Modeling (BIM), and interactive web and VR presentations, show promising advancements, AI still struggles with complex architectural functions. AI lacks the creativity and imagination inherent in human cognition. It operates based on fixed programming, producing specific outcomes and requiring human oversight to apply insights from one dataset to another. The primary challenge in using AI for architectural design is ensuring minimal design flaws, as replicating human cognitive abilities with AI and various machine learning techniques remains difficult. This research paper aims to explore the relationship between cognitive science, artificial intelligence, and the architectural design process through four main objectives: First, to investigate the integration of AI with current architectural software applications. Second, to examine potential connections between AI and major architectural design trends. Third, to define two frameworks for the Cognitive Architectural Design Process to guide the development of AI systems in architectural design by analyzing key cognitive design theories. Finally, to create a proposed "Architectural Design Process-Cognitive Pilot Map" from an architectural perspective to aid AI programmers in developing architecture design software applications.

The Impact of Employee Satisfaction on Firm Profitability: A Focus on Employee Performance and Customer Satisfaction

This thesis endeavors to conduct a comprehensive analysis of the correlation between employee satisfaction, employee performance, customer satisfaction, and firm profitability. In a contemporary business landscape where employee satisfaction is increasingly acknowledged as a pivotal determinant of organizational success, this study aims to elucidate the intricate dynamics governing this relationship. By meticulously scrutinizing existing research and empirical evidence, this research aims to shed light on how employee satisfaction influences employee performance, subsequently impacting customer satisfaction, and ultimately, firm profitability. In the swiftly evolving modern business milieu, grasping the profound implications of employee satisfaction has become an imperative for achieving sustainable growth. This investigation narrows its focus to dissect the intricate web of interactions that either propel or hinder an organization's journey towards profitability. Through a meticulous analysis of empirical data and scholarly discourse, this study underscores the pivotal role of employee satisfaction in shaping workforce influencing customer perceptions, and, consequently, augmenting a company's financial well-being. As we navigate this exploration, it becomes increasingly evident that employee satisfaction constitutes a cornerstone of organizational prosperity.

How does anthropogenic food influence the trophic ecology of Rocky Mountain Red Fox?

Abstract Providing novel food subsidies to wildlife can influence behavior, resource use, disease dynamics, and food web interactions. Studies examining impacts of anthropogenic food have primarily occurred in urban landscapes where anthropogenic resources are consistently accessible. National parks, however, experience similar issues regarding wildlife exploiting anthropogenic food, but access to anthropogenic food is contingent on human visitation, which can fluctuate dramatically between seasons. We evaluated how fluctuating availability of anthropogenic food and demographic factors influenced the isotopic niche of Rocky Mountain Red Fox (Vulpes vulpes macroura) at the population and individual level in Grand Teton National Park, Wyoming. From 2016 to 2021, we assessed diet-related questions by collecting 55 whisker samples and 52 hair samples from 40 unique individuals and analyzed them using stable isotope analysis (δ13C and δ15N). We discovered that Rocky Mountain red foxes have a broad isotopic niche, with seasonal differences in their consumption of anthropogenic food. Contrary to our expectations, foxes demonstrated increased reliance on anthropogenic food (higher δ13C values) during winter months, whereas natural food consumption or dietary mixing was more prominent in summer months. Natural food scarcity could be driving foxes to seek out more anthropogenic food in the winter, whereas the increased abundance of natural food items in the summer could result in a lower need for foxes to supplement their diet with anthropogenic food. Adults had consistently higher δ13C values relative to juveniles, indicating either intraspecific variation in boldness or dominance leading to increased exploitation of anthropogenic food, which could be a learned behavior coinciding with habituation. Finally, we observed that increasing densities of human features within the home range of a fox was a strong predictor of anthropogenic food reliance at the individual level. Our work provided a deeper understanding of the trophic ecology of Rocky Mountain Red Fox in relation to human activity in a nature preserve, and equipped managers with insight into potential patterns associated with food-conditioned foxes.

The Identification of New Pharmacological Targets for the Treatment of Glaucoma: A Network Pharmacology Approach

Background: Glaucoma is a progressive optic neuropathy characterized by the neurodegeneration and death of retinal ganglion cells (RGCs), leading to blindness. Current glaucoma interventions reduce intraocular pressure but do not address retinal neurodegeneration. In this effort, to identify new pharmacological targets for glaucoma management, we employed a network pharmacology approach. Methods: We first retrieved transcriptomic data from GEO, an NCBI database, and carried out GEO2R (an interactive web tool aimed at comparing two or more groups of samples in a GEO dataset). The GEO2R statistical analysis aimed at identifying the top differentially expressed genes (DEGs) and used these as input of STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) app within Cytoscape software, which builds networks of proteins starting from input DEGs. Analyses of centrality metrics using Cytoscape were carried out to identify nodes (genes or proteins) involved in network stability. We also employed the web-server software MIRNET 2.0 to build miRNA–target interaction networks for a re-analysis of the GSE105269 dataset, which reports analyses of microRNA expressions. Results: The pharmacological targets, identified in silico through analyses of the centrality metrics carried out with Cytoscape, were rescored based on correlations with entries in the PubMed and clinicaltrials.gov databases. When there was no match (82 out of 135 identified central nodes, in 8 analyzed networks), targets were considered “potential innovative” targets for the treatment of glaucoma, after further validation studies. Conclusions: Several druggable targets, such as GPCRs (e.g., 5-hydroxytryptamine 5A (5-HT5A) and adenosine A2B receptors) and enzymes (e.g., lactate dehydrogenase A or monoamine oxidase B), were found to be rescored as “potential innovative” pharmacological targets for glaucoma treatment.

Development and distribution of an in situ experimental wind turbine noise database

The PIBE project is the first French collaborative research project on wind turbine noise. One of its objectives is to quantify the experimental dispersion observed in situ on acoustic quantities/metrics and influencing parameters, and to compare it with the numerical dispersion estimated using acoustic propagation models. A long-term experimental campaign was carried out over consecutive 410 days around a wind farm comprising eight 80-metre-high and 90-metre diameter turbines. Acoustic sensors (five Class I sound level meters) were deployed on site, recording third-octave spectra and overall A- and Z-weighted values of the Leq indicator and fractile indices (L10, L50 and L90), at distances from 325 m to 1400 m from the wind turbines row. In addition, three 3D ultrasonic anemometers and a Lidar system were used to measure meteorological variables influencing long-range sound propagation (e.g. wind and temperature verical profiles). Besides, train and aircraft passing close to the site were inventoried to identify periods of high background noise. All experimental data have been processed into an ElasticSearch database. An interactive web application has been developed in R Shiny to facilitate processing, visualization and analysis of the experimental database.

Stable isotope analysis of western Lake Superior predatory fishes, part one: Trophic niche overlap

Characterizing food web interactions between introduced and native fish predators is important to quantify niche overlap, assess predator–prey balance, and support fisheries management. Lake Superior provides an ideal setting to investigate potential trophic overlap between native top predators, lake trout (Salvelinus namaycush) and walleye (Sander vitreus), and a diverse assemblage of introduced salmonids. Angler-caught fish were used to measure trophic position and niche overlap between predatory fishes in the western arm of Lake Superior based on carbon and nitrogen stable isotope ratios (δ13C, δ15N). Within a species, we did not find consistent differences in either δ13C or δ15N values by sex, collection year, capture location, or length. Among species, the range in δ15N values was >5 ‰, indicating that these species occupy ∼2 trophic positions, with dietary reliance ranging from primarily invertebrates to primarily fish, whereas the range in δ13C values indicated dietary reliance on a mix of pelagic and benthic prey. Combined, the δ13C and δ15N values revealed siscowet lake trout as the apex predator having a distinct trophic niche, while walleye and lean lake trout were intermediate trophic position predators with overlapping isotopic niches, and introduced salmonids were the lowest trophic position predators with overlapping trophic niches. Overlapping trophic niches indicated similar resource reliance and habitat occupancy among native lake trout and walleye, as well as among introduced salmonids, but less so between native and introduced predators.

μREACT: A microfluidic system for rapid evaluation of trans-kingdom interactions

Trans-kingdom interactions between cells play pivotal roles in shaping intricate ecological and biological networks. However, our grasp of these interactions remains incomplete. Specifically, the vast phylogenetic spectrum of microorganisms capable of interacting with a given host cell type remains obscure, primarily due to the absence of efficient, high-throughput, single-cell resolution systems that can rapidly decipher these interactions. Here, we introduce μREACT (Microfluidic system for Rapid Evaluation of bacterial Adherence and Communication in Trans-kingdom interactions), a microfluidic system designed to analyze interkingdom interactions. μREACT not only unveiled both recognized and previously unknown interactions but also enabled their detailed characterization. The system features the use of microfluidic dielectrophoretic separation of bacteria that adhere to host cells at single-cell (digital) resolution, and enabled the sorting of 107 adherent microorganisms per hour, representing a comparable throughput to conventional flow cytometry systems, but without requiring any labeling. The analysis of soil microbial samples using μREACT revealed several bacterial species previously known to have high adherence to mammalian host cells, as well as new interactions involving strains that displayed hallmarks of emerging endosymbiosis. Taken together, μREACT serves as a formidable tool for identifying and characterizing webs of interkingdom interactions. Its implications extend beyond discovery of such interactions, where it has the potential to provide new insights into fundamental mechanisms driving ecosystem dynamics and biological processes.

Normalizing and Mainstreaming the French Radical Right: Divergences in Leadership Communication during a Summer of Inland and Borderland Tensions

Abstract The radical right has become a central political force in most Western democracies. This process has been the result of the normalization and mainstreaming of its political leaders, discourses, and visions of society, notably involving the scapegoating of immigration and the use of the Great Replacement conspiracy theory. However, the normalization and mainstreaming of radical right actors competing for the leadership of their overall political family remain an under-researched topic. The scope of the current article is to explore this phenomenon by considering the case of France, which after the United States, is the largest Western state that could potentially be ruled by a radical right president with extensive executive powers. The analysis shows that actors competing for the leadership of the radical right in a given country can generate diverging strategies of normalization and mainstreaming to secure their political distinction. Immigration and the Great Replacement constitute, respectively, a topic and a conspiracy theory that are emphasized and/or downplayed by opportunistic stakeholders weaving a web of interactions to define their comparative legitimacy and supremacy in the public sphere.