Search Results (731)

Wildlife–vehicle collisions (WVCs) remain a significant cause of animal mortality worldwide, particularly in regions experiencing rapid road network expansion. During the COVID-19 pandemic, a number of studies reported decreased WVC rates, attributing this trend to reduced traffic volumes. However, the validity of the simplified assumption that “fewer vehicles means fewer collisions” remains underexplored from a mechanistic perspective. This study aims to reevaluate that assumption using two simulation-based models that incorporate both the physics of vehicle movement and behavioral parameters of road-crossing animals. Employing an inverse modeling approach with quasi-realistic traffic scenarios, we quantify how vehicle speed, spacing, and animal hesitation affect collision likelihood. The results indicate that approximately 10% of modeled cases contradict the prevailing assumption, with collision risk peaking at intermediate traffic densities. These findings challenge common interpretations of WVC dynamics and underscore the need for more refined, behaviorally informed mitigation strategies. We suggest that integrating such approaches into road planning and conservation policy—particularly under the European Union’s ‘Vision Zero’ framework—could help reduce wildlife mortality more effectively in future scenarios, including potential pandemics or mobility disruptions. Full article

Despite the current level of public immunity to SARS-CoV-2, the early inflammatory events associated with respiratory distress in COVID-19 patients are not fully elucidated. Syrian golden hamsters, facultative hibernators, recapitulate the phenotype of SARS-CoV-2-induced severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—induced severe acute lung injury seen in patients. In this study, we describe the predominance of the innate immune response in hamsters inoculated with four different SARS-CoV-2 variants, underscoring phenotypic differences among them. Severe inflammatory lung injury was chronologically associated with acute and significant weight loss, mainly in animals inoculated with A.2 and Delta variants. Omicron-infected animals had lower overall histopathology scores compared to other variants. We highlight the central role of endothelial injury and activation in the pathogenesis of experimental SARS-CoV-2 infection in hamsters, characterised by the presence of proliferative type I and type II pneumocytes with abundant surfactant expression, thereby maintaining hyperinflated alveolar fields. Additionally, there was evidence of intrapulmonary lymphatic vessel proliferation, which was accompanied by a lack of detectable microthrombosis in the lung parenchyma. However, white microthrombi were observed in lymphatic vessels. Our findings suggest that the physiological compensatory mechanisms that maintain respiratory homeostasis in Golden Syrian hamsters prevent severe respiratory distress and death after SARS-CoV-2 infection. Full article

Introduction: The gut microbiota is vital for human health, and its modulation through dietary and pharmaceutical compounds has gained increasing attention. Among gut microbes, Akkermansia muciniphila has been extensively researched due to its role in maintaining intestinal barrier integrity, regulating energy metabolism, and influencing inflammatory responses. Subject: To analyze and synthesize the available scientific evidence on the influence of various bioactive compounds, including prebiotics, polyphenols, antioxidants, and pharmaceutical agents, on the abundance and activity of A. muciniphila, considering underlying mechanisms, microbial context, and its therapeutic potential for improving metabolic and intestinal health. Methods: A systematic literature review was conducted in accordance with the PRISMA 2020 guidelines. Databases such as PubMed, ScienceDirect, Scopus, Web of Science, SciFinder-n, and Google Scholar were searched for publications from 2004 to 2025. Experimental studies in animal models or humans that evaluated the impact of bioactive compounds on the abundance or activity of A. muciniphila were prioritized. The selection process was managed using the Covidence platform. Results: A total of 78 studies were included in the qualitative synthesis. This review compiles and analyzes experimental evidence on the interaction between A. muciniphila and various bioactive compounds, including prebiotics, antioxidants, flavonoids, and selected pharmaceutical agents. Factors such as the chemical structure of the compounds, microbial environment, underlying mechanisms, production of short-chain fatty acids (SCFAs), and mucin interactions were considered. Compounds such as resistant starch type 2, GOS, 2′-fucosyllactose, quercetin, resveratrol, metformin, and dapagliflozin showed beneficial effects on A. muciniphila through direct or indirect pathways. Discussion: Variability across studies reflects the influence of multiple variables, including compound type, dose, intervention duration, experimental models, and analytical methods. These differences emphasize the need for a contextualized approach when designing microbiota-based interventions. Conclusions: A. muciniphila emerges as a promising therapeutic target for managing metabolic and inflammatory diseases. Further mechanistic and clinical studies are necessary to validate its role and to support the development of personalized microbiota-based treatment interventions. Full article

Background: Neurodevelopmental disorders, including autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), are increasingly recognized as conditions arising from multifaceted interactions among genetic predisposition, environmental exposures, and epigenetic modifications. Among epigenetic mechanisms, non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and PIWI-interacting RNAs (piRNAs), have gained attention as pivotal regulators of gene expression during neurodevelopment. These RNA species do not encode proteins but modulate gene expression at transcriptional and post-transcriptional levels, thereby influencing neuronal differentiation, synaptogenesis, and plasticity. Objectives: This systematic review critically examines and synthesizes the most recent findings, particularly in the post-COVID transcriptomic research era, regarding the role of ncRNAs in the pathogenesis, diagnosis, and potential treatment of neurodevelopmental disorders. Methods: A comprehensive literature search was conducted to identify studies reporting on the expression profiles, functional implications, and clinical relevance of ncRNAs in neurodevelopmental disorders, across both human and animal models. Results: Here, we highlight that multiple classes of ncRNAs are differentially expressed in individuals with ASD and ADHD. Notably, specific miRNAs and lncRNAs demonstrate potential as diagnostic biomarkers with high sensitivity and specificity. Functional studies further reveal that ncRNAs actively contribute to pathogenic mechanisms by modulating neuronal gene networks. Conclusions: Emerging experimental data indicate that the exogenous administration of certain ncRNAs may reverse molecular and behavioral phenotypes, supporting their therapeutic promise. These findings broaden our understanding of neurodevelopmental regulation and open new avenues for personalized diagnostics and targeted interventions in clinical neuropsychiatry. Full article

The COVID-19 pandemic has significantly altered consumer habits, particularly in relation to food choices. In this context, plant-based diets have gained prominence, driven by health, environmental, and ethical considerations. This study investigates the primary motivational and inhibitory factors influencing the consumption of plant-based foods among residents of the Galicia–Northern Portugal Euroregion. Utilizing the Theory of Reasoned Action, an extended model was proposed and tested through a quantitative survey. A total of 214 valid responses were collected via an online questionnaire distributed in Portuguese and Spanish. Linear regression analysis revealed that health awareness, animal welfare, and environmental concern significantly shape positive attitudes, which subsequently affect the intention to consume plant-based foods. Additionally, perceived barriers—such as lack of taste and insufficient information—were found to negatively influence intention. These findings contribute to the consumer behavior literature and provide strategic insights for stakeholders aiming to promote more sustainable dietary patterns in culturally connected cross-border regions. Full article

Zoonotic diseases are transmitted from animals to humans, and they impose a significant global burden by impacting both animal and human health. It can lead to substantial economic losses and cause millions of human deaths. The emergence and re-emergence of zoonotic diseases are heavily influenced by both anthropogenic and natural drivers such as climate change, rapid urbanization, and widespread travel. Over time, the unprecedented rise of new and re-emerging zoonotic diseases has prompted the need for rapid and effective vaccine development. Following the success of the COVID-19 mRNA vaccines, mRNA-based platforms hold great promise due to their rapid design, swift development and ability to elicit robust immune responses, thereby highlighting their potential in combating emerging and pre-pandemic zoonotic viruses. In recent years, several mRNA vaccines targeting emerging and re-emerging zoonotic viral diseases, such as rabies, Nipah, Zika, and influenza, have advanced to clinical trials, demonstrating promising immunogenicity. This review explores recent advances, challenges, and future directions in developing mRNA vaccines against emerging and re-emerging zoonotic viral diseases. Full article

In the wake of the COVID-19 pandemic and amid growing concerns regarding viral threats such as avian influenza, Mpox, and HKU5 bat coronaviruses, the phenomenon of viral zoonotic spillover, when viruses leap from circulation in non-human animals to humans, has garnered unprecedented global attention [...] Full article

There is increasing recognition of the importance of human–animal interaction (HAI) research in the assessment of animal welfare. This is partly reflected by the appearance of increasing animal–visitor interaction (AVI) publications in zoos. Early AVI publications primarily focused on primates and the impact of visitors on animals (visitor effects), with most identifying negative welfare impacts. This review aims to identify trends and changes in the key factors of AVIs (e.g., types of interactions measured; taxa studied; welfare impact). Covidence online software and PRISMA were used to screen papers and extract data. A total of 157 papers comprising 314 studies were included. AVI publications have increased in the last two decades, with a large increase in publications since 2020. Most publications have focused on visitor effects, as opposed to the impact of animals on visitors (visitor experiences). Earlier visitor effect studies mostly focused on primates, while more recent studies have primarily focused on non-primate species. Excluding studies categorized as neutral, there were more visitor effect studies with measures focused on negative than positive welfare impacts. However, the last decade and a half has seen a substantial increase in visitor effect studies measuring positive welfare impacts. These results are discussed in reference to growing changes in the types of studies, species, and outcomes measured in AVIs. In addition, we consider the future of AVI research, including a growing need for and consideration of standardized welfare assessments, the increased use of experimental control, and AVIs that equally promote visitor education and positive animal welfare. Full article

While there are many postulates for the etiology of post-viral chronic fatigue and other symptomatology, little is known. We draw on our past experience of these syndromes to devise means which can expose the primary players of this malady in terms of a panoply participating biomolecules and the state of the stool microbiome. Using databases established from a large dataset of patients at risk of colorectal cancer who were followed longitudinally over 3 decades, and a smaller database dedicated to building a Long PASC cohort (Post-Acute Sequelae of COVID-19), we were able to ascertain factors that predisposed patients to (and resulted in) significant changes in various biomarkers, i.e., the stool microbiome and serum cytokine levels, which we verified by collecting stool and serum samples. There were significant changes in the stool microbiome with an inversion from the usual Bacillota and Bacteroidota species. Serum cytokines showed significant differences in MIP-1β versus TARC (CC chemokine ligand 17) in patients with either PASC or COVID-19 (p < 0.02); IL10 versus IL-12p70a (p < 0.02); IL-1b versus IL-6 (p < 0.01); MCP1 versus TARC (p < 0.03); IL-8 versus TARC (p < 0.002); and Eotaxin3 versus TARC (p < 0.004) in PASC. Some changes were seen solely in COVID-19, including MDC versus MIP-1α (p < 0.01); TNF-α versus IL-1-β (p < 0.06); MCP4 versus TARC (p < 0.0001). We also show correlates with chronic fatigue where an etiology was not identified. These findings in patients with positive criteria for PASC show profound changes in the microbiome and serum cytokine expression. Patients with chronic fatigue without clear viral etiologies also have common associations, including a history of tonsillectomy, which evokes a likely immune etiology. Full article

Background/Objectives: Accurate classification of COVID-19 from chest X-rays is critical but remains limited by overlapping features with other lung diseases and the suboptimal performance of current methods. This study addresses the diagnostic gap by introducing a novel hybrid framework for precise segmentation and classification of lung conditions. Methods: The approach combines multi-level thresholding with the advanced metaheuristic optimization algorithms animal migration optimization (AMO), electromagnetism-like optimization (EMO), and the harmony search algorithm (HSA) to enhance image segmentation. A convolutional neural network (CNN) is then employed to classify segmented images into COVID-19, viral pneumonia, or normal categories. Results: The proposed method achieved high diagnostic performance, with 99% accuracy, 99% sensitivity, and 99.5% specificity, confirming its robustness and effectiveness in clinical image classification tasks. Conclusions: This study offers a novel and technically integrated solution for the automated diagnosis of COVID-19 and related lung conditions. The method’s high accuracy and computational efficiency demonstrate its potential for real-world deployment in medical diagnostics. Full article

Background/Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Disease 2019 (COVID-19), has rapidly evolved, giving rise to multiple Variants of Concern—including Alpha, Beta, Gamma, Delta, and Omicron—which emerged independently across different regions. Licensed COVID-19 vaccines primarily target the highly mutable spike protein, resulting in reduced efficacy due to immune escape by emerging variants. Previously, we developed a live attenuated Francisella tularensis LVS ΔcapB single-vector platform COVID-19 vaccine, rLVS ΔcapB/MN, expressing the conserved membrane (M) and nucleocapsid (N) proteins from the early SARS-CoV-2 WA-01/2020 strain. In this study, we evaluate the efficacy of rLVS ΔcapB/MN and an enhanced version, rLVS ΔcapB::RdRp/MN, which additionally expresses the conserved RNA-dependent RNA polymerase (RdRp) protein from the same strain, in a hamster model. Methods: Both vaccine candidates were administered orally or intranasally to golden Syrian hamsters (equal numbers of males and females) and evaluated against intranasal challenge with SARS-CoV-2 Delta (B.1.617.2-AY.1) and Omicron (BA.5) variants. Results: Vaccinated animals developed robust, TH1-biased IgG responses specific to the nucleocapsid protein. Following SARS-CoV-2 challenge, immunized hamsters exhibited reduced weight loss, lower oropharyngeal and lung viral titers, and improved lung pathology scores compared with unvaccinated controls. Conclusion: These findings support the potential of this universal vaccine to provide broad protection against current and future SARS-CoV-2 variants, with minimal need for updating. Full article

Decreases in animal mortality due to wildlife–vehicle collisions have been consistently documented as an environmental effect of human mobility restrictions aimed at containing the spread of the COVID-19 pandemic. In this study, we investigate this phenomenon on the mid-sized Mediterranean island of Lesvos, considering a multi-species group of mammals over a five-year systematic recording of animal casualties. We developed a method to analyze the relationship between actual casualties and risk, drawing inspiration from Markowitz’s theory on multi-asset optimization in economics. Additionally, we treated this phenomenon as a Poisson probabilistic process. Our main finding indicates that the lockdown year diverged markedly in modeled return–risk space, exhibiting a displacement on the order of 10² compared to the multi-year baseline—an outcome that reflects structural changes in risk dynamics, not a literal 100-fold decrease in observed counts. This modeled shift is significantly larger compared to published evidence regarding individual species. The results concerning the vulnerability of specific mammals, analyzed as a Poisson process, underscore the importance of singular events that can overshadow the overall systemic nature of the issue. We conclude that a promising strategy for addressing this problem is for conservationists to integrate animal-friendly measures into general human road safety policies. Full article

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the zoonotic virus responsible for the COVID-19 pandemic, has caused global health and economic disruption. American mink (Neovison vison) are highly susceptible to SARS-CoV-2 and capable of transmitting it to both mink and humans. We previously reported the first detection of SARS-CoV-2 in feral mink, with two positive cases among 13 animals in the upper courses of two rivers in the Valencian Community, eastern Spain. Here, we expand that study with 60 additional feral mink sampled from November 2020 to May 2022. Four new positives were identified by two-step RT-PCR assay on necropsy samples, including nasal and rectal swabs, lung tissue, lymph nodes, and fetuses from three pregnant females. In total, six of 73 mink tested positive, all with low viral loads. Sanger sequencing confirmed infection and revealed clustering with the B.1.177 and Alpha variants. Body weight and reproductive status analyses indicated seasonal breeding and high population turnover, consistent with other wild mink populations. Our findings reveal that SARS-CoV-2 circulation is limited in feral mink, at least in this region. They underscore the key importance of wildlife surveillance as an element of the One Health strategy, which encompasses humans, animals, and the environment. Full article

Background: Emerging and re-emerging infectious diseases (EIDs and Re-EIDs) cause significant economic crises and public health problems worldwide. Epidemics appear to be more frequent, complex, and harder to prevent. Early warning systems can significantly reduce outbreak response times, contributing to better patient outcomes. Improving early warning systems and methods might be one of the most effective responses. This study employs a bibliometric analysis to dissect the global research hotspots and evolutionary trends in the field of infectious disease early warning, with the aim of providing guidance for optimizing public health emergency management strategies. Methods: Publications related to the role of early warning systems in detecting and responding to infectious disease outbreaks from 1999 to 2024 were retrieved from the Web of Science Core Collection (WoSCC) database. CiteSpace software was used to analyze the datasets and generate knowledge visualization maps. Results: A total of 798 relevant publications are included. The number of annual publications has sharply increased since 2000. The USA produced the highest number of publications and established the most extensive cooperation relationships. The Chinese Center for Disease Control & Prevention was the most productive institution. Drake, John M was the most prolific author, while the World Health Organization and AHMED W were the most cited authors. The top two cited references mainly focused on wastewater surveillance of SARS-CoV-2. The most common keywords were “infectious disease”, “outbreak”, “transmission”, “virus”, and “climate change”. The basic keyword “climate” ranked the first and long duration with the strongest citation burst. “SARS-CoV-2”, “One Health”, “early warning system”, “artificial intelligence (AI)”, and “wastewater-based epidemiology (WBE)” were emerging research foci. Conclusions: Over the past two decades, research on early warning of infectious diseases has focused on climate change, influenza, SARS, virus, machine learning, warning signals and systems, artificial intelligence, and so on. Current research hotspots include wastewater-based epidemiology, sewage, One Health, and artificial intelligence, as well as the early warning and monitoring of COVID-19. Research foci in this area have evolved from focusing on climate–disease interactions to pathogen monitoring systems, and ultimately to the “One Health” integrated framework. Our research findings underscore the imperative for public health policymakers to prioritize investments in real-time surveillance infrastructure, particularly wastewater-based epidemiology and AI-driven predictive models, and strengthen interdisciplinary collaboration frameworks under the One Health paradigm. Developing an integrated human–animal–environment monitoring system will serve as a critical development direction for early warning systems for epidemics. Full article

Pet ownership is the most common form of human–animal interaction (HAI), is prevalent worldwide and confers benefits for the health and wellbeing of humans. Here, we examined a large set of anonymised data from the Royal Society for the Prevention of Cruelty to Animals (RSPCA) to identify trends in the intake, adoption and relinquishment of companion animals in England and Wales before and during times of uncertainty, namely, the COVID-19 pandemic and the cost-of-living crisis (COLC). We employed an interrupted time series (ITS) design which controls for pre-existing trends by comparing observed outcomes post-intervention with those expected if the intervention had not occurred. Nearly 200,000 animals were taken in by the RSPCA and over 140,000 animals were adopted or released over the four-year period from 2018 to 2022. When controlling for the brief closure of RSPCA sites, fewer dogs and cats were taken in and adopted during the pandemic compared to pre-pandemic, and the intake and adoption of animals were lower during the COLC than before. A downward trend in the return of animals was observed, and the principal reasons for return were problem behaviours, owner unpreparedness and a change in circumstances. Our ITS analysis also permitted forecast predictions to be made which could prove helpful to the RSPCA. Full article