Search Results (4,044)

The Mycoplasmataceae are a family of bacteria that typically cause respiratory, arthritic, and genitourinary disease in humans. Mycoplasma spp. of animal origin are also the causative agents of porcine wheezing disease, chronic respiratory disease and arthritis in chickens and other conditions. These diseases have a significant impact on public health and the economic development of livestock breeding. Clinical prevention and treatment of mycoplasma infections is primarily dependent on the use of antibiotics. However, inappropriate and excessive use of antimicrobials has enabled resistance development that has become a significant clinical concern. Mycoplasma are also robust biofilm producers, and this process is a major factor for the persistence of these infections, especially in conjunction with common antibiotic resistance mechanisms, including target gene mutations and the action of efflux pumps. A mycoplasma biofilm refers to a structured and stable microbial community formed by Mycoplasma spp. adhering to biological or non-biological surfaces under suitable conditions and secreting extracellular polymers (EPS) such as polysaccharides. This process allows the microorganisms to adapt to their surrounding environment and survive during the growth process. These biofilms render bacteria more resistant to antimicrobials than planktonic bacteria, resulting in biofilm-associated infections that are more challenging to eradicate and more likely to recur. The current study reviews progress from the fields of biofilm formation, structure and identification, correlations between biofilms and drug resistance and virulence as well as methods of biofilm prevention and control. Our aim was to provide a reference basis for the subsequent in-depth understanding of the research of mycoplasma biofilms. Full article

White-tailed deer (Odocoileus virginianus) are a cervid species native to the Americas with ecological, social, and economic significance. Managers must consider several factors when working to maintain the health and sustainability of these wild herds, including reproduction, particularly pregnancy and recruitment rates. White-tailed deer have a variable reproductive capacity, with age, health, and habitat influencing this variability. However, it is unknown whether chronic wasting disease (CWD) impacts reproduction and, more specifically, if CWD infection alters a female deer’s probability of pregnancy. Our study addressed this question using data from 9783 female deer culled in northern Illinois between 2003 and 2023 as part of the Illinois Department of Natural Resources’ ongoing CWD management program. Multilevel Bayesian logistic regression was employed to quantify the relationship between pregnancy probability and covariates like maternal age, deer population density, and date of culling. Maternal infection with CWD was found to have no significant effect on pregnancy probability, raising concerns that the equal ability of infected and non-infected females to reproduce could make breeding, which inherently involves close physical contact, an important source of disease transmission between males and females and females and their fawns. The results also identified that female fawns (<1 year old) are sensitive to county-level deer land cover utility (LCU) and deer population density, and that there was no significant difference in how yearlings (1–2 years old) and adult (2+ years old) responded to these variables. Full article

Rabies remains a significant global public health concern, causing an estimated 59,000–69,000 human fatalities annually. Despite being entirely preventable through vaccination, rabies continues to impose substantial economic burdens worldwide. This study presents a scoping review of the economic research on rabies to determine overlaps and gaps in knowledge and inform future research strategies. We selected 150 studies (1973–2024) to analyze. The review categorizes the literature based on geographic distribution, species focus, and type of study. Findings indicate that economic studies are disproportionately concentrated in developed countries, such as the United States and parts of Europe, where rabies risk is low, while high-risk regions, particularly in Africa and Asia, remain underrepresented. Most studies focus on dog-mediated rabies, reflecting its dominant role in human transmission, while fewer studies assess the economic impacts of wildlife and livestock-mediated rabies. Case studies and modeling approaches dominate the literature, whereas cost–benefit and cost–effectiveness analyses—critical for informing resource allocation—are limited. The review highlights the need for more economic evaluations in rabies-endemic regions, expanded research on non-dog reservoirs, and broader use of economic methods. Addressing these gaps will be crucial for optimizing rabies control and supporting global initiatives to eliminate dog-mediated rabies by 2030. Full article

The COVID-19 pandemic was a profoundly influential global occurrence in recent history, impacting daily life, economics, and healthcare systems for an extended period. The abundance of data has been essential in creating models to simulate and forecast the dissemination of infectious illnesses, aiding governments and health organizations in making educated decisions. This research primarily focuses on designing a control technique that incorporates the five most important inputs that impact the spread of COVID-19 on the Romanian territory. Quantitative analysis and data filtering are two crucial aspects to consider when developing a mathematical model. In this study the transfer function principle was used as the most accurate method for modeling the system, based on its superior fit demonstrated in a previous study. For the control strategy, a PI (Proportional-Integral) controller was designed to meet the requirements of the intended behavior. Finally, it is showed that for such complex models, the chosen control strategy, combined with fine tuning, led to very accurate results. Full article

For a long time, the explanation of the various determinants of oil price fluctuations and their impact on economic activity has been based on the supply and demand mechanism. However, with various volatile changes in the international situation in recent years, such as threats to public health and an increase in regional conflicts, special attention has been paid to the geopolitical context as an additional driver of oil price fluctuations. This study examines the relationship between oil price changes and GDP growth and other macroeconomic variables from the perspective of the vulnerability of oil-importing and oil-exporting countries to unexpected oil price shocks, driven by tense geopolitical events, in three European countries (Norway, Germany, and Poland). We apply the Structural Vector Autoregressive (SVAR) model and orthogonalized impulse response functions, based on quarterly data, in regard to two samples: the first spans 1995Q1–2019Q4 (pre-2020 sample), with relatively gradual changes in oil prices, and the second spans 1995Q1–2024Q2 (whole sample), with sudden fluctuations in oil prices due to geopolitical developments. A key finding of this research is that vulnerability to unpredictable oil price shocks related to geopolitical tensions is higher than in regard to expected gradual changes in oil prices, both in oil-importing and oil-exporting countries. Different causality patterns and stronger responses in regard to GDP growth during the period, including in regard to tense geopolitical events in comparison to the pre-2020 sample, lead to the belief that economies are not more resilient to oil price shocks as has been suggested by some studies, which referred to periods that were not driven by geopolitical events. Our research also suggests that countries implementing policies to reduce oil dependency and promote investment in alternative energy sources are better equipped to mitigate the adverse effects of oil price shocks. Full article

Glycyrrhiza uralensis (G. uralensis), a leguminous plant, is an important medicinal and economic plant in saline–alkaline soils of arid regions in China. Its main bioactive components include liquiritin, glycyrrhizic acid, and flavonoids, which play significant roles in maintaining human health and preventing and adjuvantly treating related diseases. However, the cultivation of G. uralensis is easily restricted by adverse soil conditions in these regions, characterized by high salinity, high alkalinity, and nutrient deficiency. This study investigated the impacts of four multistrain microbial inoculants (Pa, Pb, Pc, Pd) on the growth performance and bioactive compound accumulation of G. uralensis in moderately saline–sodic soil. The aim was to screen the most beneficial inoculant from these strains, which were isolated from the rhizosphere of plants in moderately saline–alkaline soils of the Hexi Corridor and possess native advantages with excellent adaptability to arid environments. The results showed that inoculant Pc, comprising Pseudomonas silesiensis, Arthrobacter sp. GCG3, and Rhizobium sp. DG1, exhibited superior performance: it induced a 0.86-unit reduction in lateral root number relative to the control, while promoting significant increases in single-plant dry weight (101.70%), single-plant liquiritin (177.93%), single-plant glycyrrhizic acid (106.10%), and single-plant total flavonoids (107.64%). Application of the composite microbial inoculant Pc induced no significant changes in the pH and soluble salt content of G. uralensis rhizospheric soils. However, it promoted root utilization of soil organic matter and nitrate, while significantly increasing the contents of available potassium and available phosphorus in the rhizosphere. High-throughput sequencing revealed that Pc reorganized the rhizospheric microbial communities of G. uralensis, inducing pronounced shifts in the relative abundances of rhizospheric bacteria and fungi, leading to significant enrichment of target bacterial genera (Arthrobacter, Pseudomonas, Rhizobium), concomitant suppression of pathogenic fungi, and proliferation of beneficial fungi (Mortierella, Cladosporium). Correlation analyses showed that these microbial shifts were linked to improved plant nutrition and secondary metabolite biosynthesis. This study highlights Pc as a sustainable strategy to enhance G. uralensis yield and medicinal quality in saline–alkali ecosystems by mediating microbe–plant–nutrient interactions. Full article

Leptospirosis is a globally significant zoonosis affecting animal health, productivity, and the environment. While typically associated with tropical climates, its persistence in semi-arid regions such as La Laguna, Mexico—characterized by low humidity, high temperatures, and limited water sources—remains poorly understood. Although these adverse environmental conditions theoretically limit the survival of Leptospira, high livestock density and synanthropic reservoirs (e.g., rodents) may compensate, facilitating transmission. In this cross-sectional study, blood sera from 445 dairy cows (28 herds: 12 intensive [MI], 16 semi-intensive [MSI] systems) were analyzed via microscopic agglutination testing (MAT) against 10 pathogenic serovars. Urine samples were cultured for active Leptospira detection. Risk factors were assessed through epidemiological surveys and multivariable analysis. This study revealed an overall apparent seroprevalence of 27.0% (95% CI: 22.8–31.1), with significantly higher rates in MSI (54.1%) versus MI (12.2%) herds (p < 0.001) and an estimated true seroprevalence of 56.3% (95% CI: 50.2–62.1) in MSI and 13.1% (95% CI: 8.5–18.7) in MI herds (p < 0.001). The Sejroe serogroup was isolated from urine in both systems, confirming active circulation. In MI herds, rodent presence (OR: 3.6; 95% CI: 1.6–7.9) was identified as a risk factor for Leptospira seropositivity, while first-trimester abortions (OR:10.1; 95% CI: 4.2–24.2) were significantly associated with infection. In MSI herds, risk factors associated with Leptospira seropositivity included co-occurrence with hens (OR: 2.8; 95% CI: 1.5–5.3) and natural breeding (OR: 2.0; 95% CI: 1.1–3.9), whereas mastitis/agalactiae (OR: 2.8; 95% CI: 1.5–5.2) represented a clinical outcome associated with seropositivity. Despite semi-arid conditions, Leptospira maintains transmission in La Laguna, particularly in semi-intensive systems. The coexistence of adapted (Sejroe) and incidental serogroups underscores the need for targeted interventions, such as rodent control in MI systems and poultry management in MSI systems, to mitigate both zoonotic and economic impacts. Full article

Biofilms are structured microbial communities that pose significant challenges to food safety and quality within the food-processing industry. Their formation on equipment and surfaces enables persistent contamination, microbial resistance, and recurring outbreaks of foodborne illness. This review provides a comprehensive synthesis of current knowledge on biofilm formation mechanisms, genetic regulation, and the unique behavior of multi-species biofilms. The review evaluates modern detection and monitoring technologies, including PCR, biosensors, and advanced microscopy, and compares their effectiveness in industrial contexts. Real-world outbreak data and a global economic impact analysis underscore the urgency for more effective regulatory frameworks and sanitation innovations. The findings highlight the critical need for integrated, proactive biofilm management approaches to safeguard food safety, reduce public health risks, and minimize economic losses across global food sectors. Full article

The Fusarium genus includes some of the most economically and ecologically impactful fungal pathogens affecting global agriculture and human health. Over the past 15 years, rapid advances in molecular biology, genomics, and diagnostic technologies have reshaped our understanding of Fusarium taxonomy, host–pathogen dynamics, mycotoxin biosynthesis, and disease management. This review synthesizes key developments in these areas, focusing on agriculturally important Fusarium species complexes such as the Fusarium oxysporum species complex (FOSC), Fusarium graminearum species complex (FGSC), and a discussion on emerging lineages such as Neocosmospora. We explore recent shifts in species delimitation, functional genomics, and the molecular architecture of pathogenicity. In addition, we examine the global burden of Fusarium-induced mycotoxins by examining their prevalence in three of the world’s most widely consumed staple crops: maize, wheat, and rice. Last, we also evaluate contemporary management strategies, including molecular diagnostics, host resistance, and integrated disease control, positioning this review as a roadmap for future research and practical solutions in Fusarium-related disease and mycotoxin management. By weaving together morphological insights and cutting-edge multi-omics tools, this review captures the transition into a new era of Fusarium research where integrated, high-resolution approaches are transforming diagnosis, classification, and management. Full article

Background: Faced with the profound impact of major infectious diseases on public life and economic development, humans have long sought to understand disease transmission and intervention strategies. To better explore the impact of individuals’ different coping behaviors—triggered by changes in their psychological security due to public information and external environmental changes—on the spread to infectious diseases, the model will place greater emphasis on quantifying psychological factors to make it more aligned with real-world situations. Methods: To better understand the interplay between information dissemination and disease transmission, we propose a two-layer network model that incorporates psychological safety factors. Results: Our model reveals key insights into disease transmission dynamics: (1) active defense behaviors help reduce both disease spread and information diffusion; (2) passive resistance behaviors expand disease transmission and may trigger recurrence but enhance information spread; (3) high-timeliness, low-fuzziness information reduces the peak of the initial infection but does not significantly curb overall disease spread, and the rapid dissemination of disease-related information is most effective in limiting the early stages of transmission; and (4) community structures in information networks can effectively curb the spread of infectious diseases. Conclusions: These findings offer valuable theoretical support for public health strategies and disease prevention after government information release. Full article

The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, and highlighting methodological trends at this nexus. A dataset of 268 peer-reviewed publications (2014–June 2025) was retrieved from the Web of Science Core Collection, filtered by the Business Economics category. Analytical techniques employed include Bibliometrix in R, VOSviewer, and science mapping tools such as thematic mapping, trend topic analysis, co-citation networks, and co-occurrence clustering. Results indicate an annual growth rate of 53.31%, with China leading in both productivity and impact, followed by Vietnam and the United Kingdom. The most prolific affiliations and authors, primarily based in China, underscore a concentrated regional research output. The most relevant journals include Energy Economics and Finance Research Letters. Network visualizations identified 17 clusters, with focused analysis on the top three: (1) Emission, Health, and Environmental Risk, (2) Institutional and Technological Infrastructure, and (3) Green Innovation and Sustainable Urban Development. The methodological landscape is equally diverse, with top techniques including blockchain technology, large language models, convolutional neural networks, sentiment analysis, and structural equation modeling, demonstrating a blend of traditional econometrics and advanced AI. This study not only uncovers intellectual structures and thematic evolution but also identifies underdeveloped areas and proposes future research directions. These include dynamic topic modeling, regional case studies, and ethical frameworks for AI in sustainable finance. The findings provide a strategic foundation for advancing interdisciplinary collaboration and policy innovation in green AI–finance ecosystems. Full article

As veganism becomes more popular, the number of vegan pregnant women and children is steadily increasing. During vegan pregnancy and early childhood, there is a high risk for nutrient deficiencies that may impair child development. External factors, such as healthcare advice, social networks, and social environments, that affect the diet of vegan pregnant women, parents, and their children, as well as their approach towards dietary supplementation, have not yet been investigated. Various sources of information, combined with a lack of expertise, sparse food and nutritional health literacy, and qualitatively heterogeneous information provision by medical experts, unsettle vegan pregnant women and parents and affect their dietary choices and potentially the health of their children. The VedieS study aims to investigate potential connections between external influences and associated impacts on a vegan diet and the intake of dietary supplements (DS) of pregnant women and children. Two surveys are being conducted within the study: one targeting 1000 vegan pregnant women and parents, and another targeting 60 experts in each of five healthcare groups: gynecologists, pediatricians, general practitioners, pharmacists, and dietitians. This study is the first to examine how socio-economic, social, and further informational factors influence dietary practices during vegan pregnancy and childhood. It highlights the need for reliable, expert-led guidance, as current information sources are often inconsistent and may put these vulnerable groups at risk. Full article

The present study aimed to provide Congolese refugee women with an opportunity to narrate firsthand experiences coping with resettlement challenges in the United States. Translator-assisted, face-to-face semi-structured individual interviews were conducted with newly resettled Congolese refugee women (n = 20) aged 18 and older who arrived in the United States between 2011 and 2018. All participants were receiving assistance from a resettlement agency, located in the Midwestern US, at the time of the study. Data were analyzed using descriptive coding and thematic analysis. Three overarching themes were developed, indicating that Congolese refugee women adopt three main coping mechanisms to deal with challenges they face after resettling in the United States: (1) use of social support, (2) acceptance of the situation, and (3) spirituality. Resettlement support services, such as those provided by resettlement agencies, mental health providers, and community-based organizations, should integrate both economic and cultural dimensions into their services to address the complex physiological, mental, and emotional impacts of resettlement. These services should prioritize culturally and spiritually sensitive techniques that are linguistically accessible. Full article

Acid mine drainage (AMD) remains a critical environmental challenge in South Africa due to its severe impact on water quality, ecosystems and public health. Numerous studies on AMD management, treatment and resource recovery have been conducted over the past 20 years. This study presents a comprehensive review of research activities on AMD in South Africa from 1998 to 2025, highlighting key trends, emerging challenges and future directions. The study reveals a significant focus on passive and active treatment methods, environmental remediation and the recovery of valuable resources, such as iron, rare earth elements (REEs) and gypsum. A bibliometric analysis was conducted to identify the most influential studies and thematic research areas over the years. Bibliometric tools (Biblioshiny and VOSviewer) were used to analyse the data that was extracted from the PubMed database. The findings indicate that research production has increased significantly over time, with substantial contributions from top academics and institutions. Advanced treatment technologies, the use of artificial intelligence and circular economy strategies for resource recovery are among the new research prospects identified in this study. Despite substantial progress, persistent challenges, such as scalability, economic viability and policy implementation, remain. Furthermore, few technologies have moved beyond pilot-scale implementation, underscoring the need for greater investment in field-scale research and technology transfer. This study recommends stronger industry–academic collaboration, the development of standardised treatment protocols and enhanced government policy support to facilitate sustainable AMD management. The study emphasises the necessity of data-driven approaches, sustainable technology and interdisciplinary cooperation to address AMD’s socioeconomic and environmental effects in the ensuing decades. Full article

Carbon emissions from freshwater aquaculture can exacerbate the greenhouse effect, thereby impacting human life and health. Consequently, it is of great significance to explore the carbon peak process and the role of emission reduction data in China’s freshwater aquaculture industry. This study innovatively employs the Logarithmic Mean Divisia Index model (LMDI) and the Tapio decoupling model to conduct an in-depth analysis of the relationship between carbon emissions and output values in the freshwater aquaculture industry, accurately identifying the main driving factors. Meanwhile, the global and local Moran’s I indices are introduced to analyze its spatial correlation from a new perspective. The results indicate that from 2013 to 2023, carbon emissions from China’s freshwater aquaculture industry exhibited a quasi-“N”-shaped trend, reaching a peak of 38 million tons in 2015. East China was the primary contributor to carbon emissions, accounting for 46%, while South China, Central China, and Northeast China each had an average annual share of around 14%, with Southwest, North China, and Northwest China contributing relatively small proportions. The global Moran’s I index showed a decreasing trend, with a p-value ≤ 0.0010 and a z-score > 3.3, indicating a 99% significant spatial correlation. High-high clusters were concentrated in some provinces of East China, while low-low clusters were found in Northwest, North, and Southwest China. The level of fishery economic development positively drove carbon emissions, whereas freshwater aquaculture production efficiency, industrial structure, and the scale of the aquaculture population had negative effects on carbon emissions. During the study period, carbon emissions exhibited three states: weak decoupling, strong decoupling, and expansive negative decoupling, with alternating strong and weak decoupling occurring after 2015. Full article