Ezekiel Tosin Babatunde

The toxicity of oxybenzone (benzophenone-3; BP-3), a UV filter present in coral reef waters at toxic concentrations, has been incompletely characterized for oxidative stress responses in adult cnidarians. In order to examine this, Aiptasia pallida (an anemone commonly used as a coral research model) was exposed to oxybenzone at concentrations of 0.02, 0.2, 2.0, and 3.0 mg/L for 5, 10, and 30 days (n = 4 tanks per treatment). Catalase (CAT) and superoxide dismutase (SOD) activity, glutathione levels, and the alkaline comet assay (% DNA in tail) were analyzed. CAT increased significantly at all concentrations and timepoints, with 80.6% maximum induction at 2.0 mg/L on Day 30 and a LOEC of 0.02 mg/L. SOD showed no significant response at any timepoint. The levels of glutathione increased at Day 5 for the two highest concentrations, but decreased at Day 10 for 3.0 mg/L. Genotoxic effects were significant at Days 5 and 10, with a threshold between 0.02 and 2.0 mg/L. A significant positive correlation between group mean CAT activity and % DNA in the tail contrasted with a null SOD–DNA association, identifying hydrogen peroxide, not superoxide, as the proximate genotoxic driver in adult cnidarian tissue. These results indicate that oxybenzone induces oxidative stress responses in A. pallida.

Emerging infectious diseases of animals that spread to humans (zoonoses) continue to represent a major threat to public health throughout the world. Knowledge of genetic elements that enable pathogens to navigate host shifts and species jumps is crucial for predicting and preventing zoonotic cross-species transmission. Comparative genomics, comparing whole-genome sequences across a range of hosts and pathogens, provides a powerful means to dissect the molecular determinants of zoonotic emergence. Here, we summarize and discuss recent advances in the understanding of genetic modifications that enable host switching and cross-species transmission by selected zoonotic pathogens. We review how comparative genomic analyses revealed the critical importance of factors such as receptor-binding domain evolution, immune evasion genes, and virulence determinants in improving pathogen fitness in new hosts.The review also highlights the integration of genomic data into One Health surveillance frameworks, enabling real-time monitoring, early detection, and improved outbreak response. Despite these advances, challenges including sampling bias, incomplete genomic databases, misannotation, and the complexity of predicting phenotype from genotype limit the field’s potential. Furthermore, ethical and biosafety concerns in studying high-risk zoonotic pathogens necessitate careful governance. We outline future directions, emphasizing the need for expanded wildlife sampling, longitudinal studies of host-pathogen co-evolution, and the application of artificial intelligence in zoonotic risk assessment. Building comprehensive, globally accessible genomic databases is essential for coordinated pathogen tracking and risk mitigation. Ultimately, comparative genomics is indispensable for understanding and managing zoonotic threats, and its continued advancement, integrated within interdisciplinary, data-driven One Health strategies, will be critical to preventing future pandemics.

Flooding is the most common and damaging natural disaster in Illinois, largely due to climate change and human activities. This study explores the integration of Geographic Information Systems (GIS) in flood risk management across the state, focusing on the mapping of high-risk areas along major river corridors such as the Mississippi and Illinois Rivers. By utilizing survey data drawn from federal and state agencies participating in the Illinois Silver Jackets program, the research develops an interactive GIS-based flood map that visualizes vulnerable communities and supports dynamic spatial analysis. The GIS application/tool serves several functions: identifying flood-prone zones, enhancing emergency preparedness, informing land use and infrastructure planning, and improving public risk communication. The GIS tool uses real-time, user-friendly interface enables both technical and non-technical stakeholders to easily engage with flood data, fostering community resilience and informed decision-making. The findings highlight the value of collaborative, data-driven approaches in advancing proactive flood mitigation strategies throughout Illinois.

Nigeria’s economic diversification hinges on transforming its urban centers into aesthetically vibrant, sustainable hubs, moving beyond reliance on crude oil. Advanced GeoAI technologies—encompassing satellite imagery, predictive analytics, and real-time urban monitoring—offer transformative potential to redeem the environmental aesthetics of Nigerian cities, fostering tourism, employment, and foreign exchange. Cities like Lagos, once celebrated for their cultural and architectural heritage, now grapple with aesthetic decline driven by rapid urbanization, inadequate planning, environmental degradation, and socio-economic disparities. This article critically examines the challenges undermining urban environmental quality in Nigeria, focusing on hotspot cities like Lagos, Port Harcourt, Abuja, Kano, among others, as a case study, and identifies gaps in knowledge, infrastructure, and institutional support that exacerbate these issues. Key obstacles include limited geospatial data, high costs of GeoAI adoption, technical expertise deficits, and socio-cultural resistance to technology-driven urban interventions. Employing a multidisciplinary approach such as a systematic literature review, the study proposes novel contributions to innovative solutions, integrating sustainable urban planning, inclusive governance, public participation, and advanced geospatial technologies to restore and enhance urban beauty. It highlights the role of GeoAI in enabling precise urban design, green space optimization, and infrastructure monitoring, drawing on best practices from cities like Singapore and Kigali that have successfully revitalized their urban aesthetics. However, successful implementation in Nigeria demands robust policy frameworks, capacity building, and equitable technology access to bridge systemic inequalities. Through addressing these challenges, this article provides a new roadmap for policymakers, city planners, and stakeholders to leverage GeoAI for urban renewal, ensuring Nigerian cities reclaim their aesthetic allure while fostering economic and environmental resilience. This study's recommendations underscore that structuring Nigeria’s urban environmental aesthetics requires not only technological innovation but also a commitment to social equity and community-driven urban transformation.

Fire outbreaks have long posed significant threats to human life, property, and the environment, often resulting in substantial economic and social losses. In this study, we present the design and implementation of an Internet of Things (IoT)-based fire-fighting robot developed to enhance early fire detection and automated suppression. The system was built around a microcontroller unit and integrates a suite of sensors for autonomous operation, enabling real-time fire detection. A motor driver controls the robot’s mobility, while a relay circuit manages the actuation of a direct current (DC) pump connected to a water jet spray mechanism for extinguishing fires. The robot also supports manual override functionality through a web-based interface accessible via smartphones or personal computers, incorporating a live camera feed for remote navigation and control. The prototype design increased response time by 30%, significantly improving the speed of fire suppression interventions. This improvement directly translated to a higher chance of containing fires before they escalate, reducing potential damage and increasing safety for occupants and first responders. We recommended that future developments expand the system's capabilities to address other classes of fires (e.g., Class B and C), beyond the current focus on Class A fires. Additionally, incorporating cloud-based infrastructure can improve real-time data processing, storage, analytics, and multi-location deployment, enabling smarter and more coordinated fire management.