Search Results (3,834)

(1) Background: Ixodes ricinus is responsible for the spreading of medically important pathogens. Monitoring the level of tick infection in various areas is essential for determining the potential tick-born risk. This study aimed to detect Borrelia spp. and Rickettsia spp. in I. ricinus ticks collected in urban and protected areas both in Poland and the Czech Republic. (2) Methods: Ticks were collected by flagging in the years 2016–2017. Borrelia spp. was detected using nested PCR targeting the flaB gene and Rickettsia spp. using nested PCR targeting gltA. (3) Results: In total, DNA of Borrelia spp. was detected in 25.9% of samples. Ticks collected in Poland were more infected compared to the Czech Republic and ticks collected in protected areas were more infected with Borrelia spp. than ticks collected in urban areas. The RFLP analysis showed the occurrence of B. afzelii and B. garinii in both countries, and additionally B. valaisiana, B. burgdorferi s.s., and B. miyamotoi in Poland. Rickettsia spp. was detected in 17.4% of I. ricinus, with comparable infection level in both countries; however, regional differences were observed. (4) Conclusion: The regional differences in Borrelia spp. and Rickettsia spp. prevalence in I. ricinus indicate the complexity of factors influencing the level of infection and underline the need for adaptation public health surveillance strategies in each region. Full article

The relationship between COVID-19 infections and environmental contaminants provides insight into how environmental factors can influence the spread of infectious diseases. By integrating epidemiological and environmental variables into a mathematical framework, the interaction between virus spread and the environment can be determined. The aim of this study was to evaluate the impact of atmospheric contaminants on the increase in COVID-19 infections in the city of Quito through the application of statistical tests. The data on infections and deaths allowed to identify the periods of greatest contagion and their relationship with the contaminants O₃, SO₂, CO, PM_2.5, and PM₁₀. A validated database was used, and statistical analysis was applied through five models based on simple linear regression. The models showed a significant relationship between SO₂ and the increase in infections. In addition, a moderate correlation was shown with PM_2.5, O₃, and CO, and a low relationship was shown for PM₁₀. These findings highlight the importance of having policies that guarantee air quality as a key factor in maintaining people’s health and preventing the proliferation of viral and infectious diseases. Full article

Predicting the key plume evolution features of groundwater contamination are crucial for assessing uncertainty in contamination control and remediation, while implementing detailed complex numerical models for a large number of scenario simulations is time-consuming and sometimes even impossible. This work develops surrogate models with an effective and practicable pathway for predicting the key plume evolution features, such as the distance of maximum plume spreading, of groundwater contamination with natural attenuation. The representative various scenarios of the input parameter combinations were effectively generated by the orthogonal experiment method and the corresponding numerical simulations were performed by the reliable Groundwater Modeling System. The PSO-SVM surrogate models were first developed, and the accuracy was gradually enhanced from 0.5 to 0.9 under a multi-objective condition by effectively increasing the sample data size from 54 sets to 78 sets and decreasing the input variables from 25 of all the considered parameters to a smaller number of the key controlling factors. The statistical surrogate models were also constructed with the fitting degree all above 0.85. The achieved findings provide effective generic surrogate models along with a scientific basis and investigation approach reference for the environmental risk management and remediation of groundwater contamination, particularly with limited data. Full article

Alzheimer’s disease (AD) is the most common type of dementia worldwide. The etiopathogenesis of this disease remains unknown. Currently, several hypotheses attempt to explain its cause, with the most well-studied being the cholinergic, beta-amyloid (Aβ), and Tau hypotheses. Lately, there has been increasing interest in the role of immunological factors and other proteins such as alpha-synuclein (α-syn) and transactive response DNA-binding protein of 43 kDa (TDP-43). Recent studies emphasize the role of tunneling nanotubes (TNTs) in the spread of pathological proteins within the brains of AD patients. TNTs are small membrane protrusions composed of F-actin that connect non-adjacent cells. Conditions such as pathogen infections, oxidative stress, inflammation, and misfolded protein accumulation lead to the formation of TNTs. These structures have been shown to transport pathological proteins such as Aβ, Tau, α-syn, and TDP-43 between central nervous system (CNS) cells, as confirmed by in vitro studies. Besides their role in spreading pathology, TNTs may also have protective functions. Neurons burdened with α-syn can transfer protein aggregates to glial cells and receive healthy mitochondria, thereby reducing cellular stress associated with α-syn accumulation. Current AD treatments focus on alleviating symptoms, and clinical trials with Aβ-lowering drugs have proven ineffective. Therefore, intensifying research on TNTs could bring scientists closer to a better understanding of AD and the development of effective therapies. Full article

Coal spontaneous combustion (CSC) is a multifaceted research domain that has been widely explored in the literature, ranging from analytical and numerical modeling to the development of fire suppression materials and methods. A comprehensive review of the literature has revealed several distinct research trajectories, or “roadmaps”, identified through criteria such as the volume of studies addressing each theme, the presence of review papers dedicated to a specific roadmap, and the explicit mention of coal spontaneous combustion in the title or keywords. This classification framework has outlined six primary roadmaps: (1) spread, quantification, and impact; (2) mechanisms, models, factors, and parameters; (3) experimental studies and models; (4) detection, monitoring, and prediction; (5) prevention and control; and (6) applications. While interconnections exist between these roadmaps, and all ultimately converge towards roadmap 5 (prevention and control), each roadmap constitutes a distinct research cluster. The focus of this review is on roadmap 4, specifically addressing the methods and technologies for detection, monitoring, and prediction of CSC events. This review encompasses studies published from 2010 to the present, providing a thorough examination of the various detection techniques employed, with particular emphasis on their limitations and the strategies proposed to overcome these challenges. A critical analysis highlights the key advantages and disadvantages of each category of techniques, offering insights into their practical applications and the potential for future advancements in this field. The present review aims to contribute to the refinement of detection and monitoring methods for CSC, with the goal of enhancing early detection capabilities and improving fire management strategies. Full article

Due to the lack of real-time planning for fire escape routes in large buildings, the current route planning methods fail to adequately consider factors related to the fire situation. This study introduces a real-time fire monitoring and dynamic path planning system based on an improved ant colony algorithm, comprising a hierarchical arrangement of upper and lower computing units. The lower unit employs an array of sensors to collect environmental data in real time, which is subsequently transmitted to an upper-level computer equipped with LabVIEW. Following a comprehensive data analysis, pertinent visualizations are presented. Capitalizing on the acquired fire situational awareness, a propagation model for fire spreading is developed. An enhanced ant colony algorithm is then deployed to calculate and plan escape routes by introducing a fire spread model to enhance the accuracy of escape route planning and incorporating the A* algorithm to improve the convergence speed of the ant colony algorithm. In response to potential anomalies in sensor data under elevated temperature conditions, a correction model for data integrity is proposed. The real-time depiction of escape routes is facilitated through the integration of LabVIEW2018 and MATLAB2023a, ensuring the dependability and safety of the path planning process. Empirical results demonstrate the system’s capability to perform real-time fire surveillance coupled with efficient escape route planning. When benchmarked against the traditional ant colony algorithm, the refined version exhibits expedited convergence, augmented real-time performance, and effectuates an average reduction of 17.1% in the length of the escape trajectory. Such advancements contribute significantly to enhancing evacuation efficiency and minimizing potential casualties. Full article

The warming trend of the Mediterranean region is already well known, but there is still a lack of information on its seasonal/annual to multidecadal time scales and its distribution in all water masses, including deep water. New temporal and spatial evidence of this thermal variability has been presented in the Tyrrhenian Sea, thanks to twenty-year continuous monitoring by eXpendable BathyThermographs (XBTs) along a fixed route from Genoa to Palermo. The Tyrrhenian Sea is one of the deepest Mediterranean sub-basins (with a maximum depth of about 4000 m), but its interaction with neighbouring basins is controlled by topographical factors, such as the Sardinian Channel to the south and the Corsican Channel to the north. The way in which the warm signal, originating from the Levantine sub-basin, and entering from the south, affects the entire Tyrrhenian Basin spreading rapidly northwards is studied, considering its peculiarities, such as topography, surface circulation, and strong stratification, as well as its climate variability. The warming trend observed for the Tyrrhenian Sea is consistent with the trend for the Mediterranean Sea as a whole. However, the Tyrrhenian Sea shows some peculiar features: around 2014, a shift to a new equilibrium (warmer) state was detected, with mean values along the monitored route that were significantly higher than the previous period (from 1999 to 2013), especially for the subsurface level, from 100 to 450 m depth. Full article

The COVID-19 pandemic has underscored the necessity of implementing non-pharmaceutical interventions such as lockdowns to mitigate the spread of infectious diseases. This study aims to model the impact of lockdown measures on the progression of an epidemic. Using a combination of compartmental models, specifically a novel delay model, we analyze the effects of varying lockdown intensities and durations on disease transmission dynamics. The results highlight that timely and stringent lockdowns can significantly reduce the peak number of infections and delay the epidemic’s peak, thereby alleviating pressure on healthcare systems. Moreover, our models demonstrate the importance of appropriate lifting of lockdowns to prevent a resurgence of cases. Analytical and numerical results reveal critical thresholds for lockdown efficacy from the epidemiological point of view, which depend on such factors as the basic reproduction number (${\Re }_0$), disease duration, and immunity waning. In the case of a single outbreak with permanent immunity, we analytically determine the optimal proportion of isolated people which minimizes the total number of infected. While in the case of temporary immunity, numerical simulations show that the infectious cases decrease with respect to the proportion of isolated people during lockdowns; as we increase the proportion of isolated people, we have to increase the duration of lockdowns to obtain periodic outbreaks. Further, we assess the influence of epidemic with or without lockdown on the economy and evaluate its economical efficacy by means of the level of population wealth. The percentage of productive individuals among isolated people influences the wealth state of the population during lockdowns. The latter increases with the rise of the former for fixed epidemic parameters. This research provides valuable insights for policymakers in designing effective lockdown strategies to control future epidemics. Full article

Background: SARS-CoV-2 vaccine uptake variation remains a significant barrier to overcoming the spread of COVID-19. Individual beliefs/attitudes about the SARS-CoV-2 vaccine vary significantly across generations due to personal experiences, access to accurate information, education levels, political beliefs, and trust in healthcare systems. Methods: This analysis used data from the baseline visit of Project 2VIDA!, a cohort of Americans of Mexican descent (AoDM) and African American individuals (n = 1052) in San Diego, CA, along the U.S.–Mexico border region. The survey assessed sociodemographics, healthcare access, socioeconomic factors, and trust in public health information/SARS-CoV-2 prevention. We conducted a logistic regression involving AoDM individuals to identify generational factors associated with completing the SARS-CoV-2 vaccine series. Results: The results of the logistic regression analysis revealed that Generation X (OR = 0.52, 95% CI = 0.33–0.82), Millennials (OR = 0.24, 95% CI = 0.14–0.41), and Generation Z (OR = 0.10, 95% CI = 0.05–0.22) were less likely to complete the SARS-CoV-2 vaccine series when compared to Baby Boomers and the Silent Generation. Conclusions: Participants with a history of SARS-CoV-2 testing and trust in the SARS-CoV-2 vaccine were significantly more likely to complete the SARS-CoV-2 vaccine series. Efforts to address vaccine series completion should be tailored to the specific concerns and motivations of different age groups. Full article

Extreme weather events are increasingly recognized as major stress factors for forest ecosystems, causing both immediate and long-term effects. This study focuses on the impacts experienced by the forests of Valdisotto, Valfurva, and Sondalo (28% of the total area is covered by forests) in Upper Valtellina (Italy) due to the Vaia storm that occurred in October 2018. To define the immediate impacts of Vaia, we assess the economic value of forest ecosystem services (ESs), particularly those provided by timber production and carbon sequestration, pre- and post-Vaia and during the emergency period. We used the market price method to assess the economic values of timber production and carbon sequestration, as these are considered to be marketable goods. Based on data processed from Sentinel-2 satellite images (with a spatial resolution of 10 m), our results show that, despite the reduction in forest area (−2.02%) and timber stock (−2.38%), the economic value of the timber production increased after Vaia due to higher timber prices (i.e., from a total of €124.97 million to €130.72 million). However, considering the whole emergency period (2019–2020), the total losses are equal to €5.10 million for Valdisotto, €0.32 million for Valfurva, and €0.43 million for Sondalo. Instead, an economic loss of 2.88% is experienced for carbon sequestration, with Valdisotto being the more affected municipality (−4.48% of the pre-Vaia economic value). In terms of long-term impacts, we discuss the enhanced impacts due to the spread of the bark beetle Ips typopgraphus. Full article

Background: Chagas disease (CD), a Neglected Tropical Disease caused by Trypanosoma cruzi, affects millions of people in Latin America and the southern US and spreads worldwide. CD results from close interactions between humans, animals, and vectors, influenced by sociodemographic factors and housing materials. Methods: This study aimed to evaluate how these factors, along with seasonal changes, affect the distribution of CD vectors in an endemic community near Puebla, Mexico, using a cross-sectional survey. A total of 383 people from this area, known for the presence of major vectors such as Triatoma barberi and Triatoma pallidipennis, were surveyed. Results: As a result of the survey, it was found that only 27.4% of respondents knew about CD, and 83.3% owned potential reservoir pets; additionally, the quality of the wall, roof, and floor significantly influenced vector sightings, while the seasonal pattern showed less of an association. Chi-square tests confirmed these associations between vector sightings and housing materials (p < 0.001); vector sightings versus seasonal patterns showed less of an association (p = 0.04), and land use changes did not show an association (p = 0.27). Conclusions: Construction materials play an important role in the sighting of triatomines in homes, so important actions should be taken to improve homes. However, further experimental or longitudinal studies are needed to establish causality. Full article

Black locust is the only host of Robinia-specialist insects in Europe. However, no study to date has examined future range shifts of specialist insects, and the relative effects of host plant availability and other factors on their range shifts. Here, we characterized the future range shifts in the host and its four specialist insects and the factors contributing to changes in their ranges. We detected substantial range expansions in all target species. Climate predictors and host plant availability were expected to have the strongest effects on the range shifts in the host and its specialist insects, respectively, suggesting that the specialist insects will track the ranges of their host. Parectopa robiniella showed the largest potential and expanding ranges and should be made a priority species for controlling invasions of Robinia-specialist insects in Europe. The expanding ranges of all specialist species were largely identified in the United Kingdom, Germany, and France, suggesting that these should be priority regions for mitigating their effects on ecosystems. Reducing future climate change is essential for preventing the spreading of specialist insects in Europe since specialist insects track their specialist host plants, and host range expansions are mainly driven by future climate changes. Full article

During the COVID-19 pandemic, wastewater surveillance was used to monitor community transmission of SARS-CoV-2. As new genetic variants emerged, the need for timely identification of these variants in wastewater became an important focus. In response to increased reports of Omicron transmission across the United States, the Oklahoma Wastewater Surveillance team utilized allele-specific RT-qPCR assays to detect and differentiate variants, such as Omicron, from other variants found in wastewater in Oklahoma. The PCR assays showed presence of the Omicron variant in Oklahoma on average two weeks before official reports, which was confirmed through genomic sequencing of selected wastewater samples. Through continued surveillance from November 2021 to January 2022, we also demonstrated the transition from prevalence of the Delta variant to prevalence of the Omicron variant in local communities. We further assessed how this transition correlated with certain demographic factors characterizing each community. Our results highlight RT-qPCR assays as a rapid, simple, and cost-effective method for monitoring the community spread of SARS-CoV-2 genetic variants in wastewater. Additionally, they demonstrate that specific demographic factors such as ethnic composition and household income can correlate with the timing of SARS-CoV-2 variant introduction and spread. Full article

Lygus pratensis (Linnaeus) is an important agricultural pest with a strong ability to move and spread between hosts. However, L. pratensis’ flight potential and factors affecting its flight ability are unclear. We used the insect flight information system (flight mill) to determine the effects of temperature, humidity, age, sex, and mating on L. pratensis’ flight ability in an artificial climate chamber. Temperature and relative humidity significantly affected L. pratensis’ flight ability; however, low and high temperature, as well as low humidity, were unsuitable, and the optimal flight environment was 20–28 °C and 60–75% RH. Lygus pratensis’ flying ability initially increased and then decreased with age and was highest at 10 days old (flight rate: 71.43%; total flight distance: 18.63 ± 1.89 km; total flight time: 6.84 ± 0.60 h). At 15 days old, flight speed was the highest (3.36 ± 0.18 km h⁻¹). Sex had little effect on L. pratensis’ flying ability; it was marginally stronger for females than males, but the difference was insignificant. Mating increased female flying ability but decreased that of males, but the difference was insignificant. Overall, L. pratensis had strong flight dispersal ability, was largely unaffected by sex and mating, and optimal flight conditions were mild temperature and humidity. This knowledge provides a scientific basis for L. pratensis outbreak prediction, prevention, and control. Full article

The significant reduction in agricultural output and the decline in product quality are two of the most glaring negative impacts caused by plant pathogenic fungi (PPF). Furthermore, contaminated food or transit might introduce mycotoxins produced by PPF directly into the food chain. Eating food tainted with mycotoxin is extremely dangerous for both human and animal health. Using fungicides is the first choice to control PPF or their toxins in food. Fungicide resistance and its effects on the environment and public health are becoming more and more of a concern, despite the fact that chemical fungicides are used to limit PPF toxicity and control growth in crops. Fungicides induce target site alteration and efflux pump activation, and mutations in PPF result in resistance. As a result, global trends are shifting away from chemically manufactured pesticides and toward managing fungal plant diseases using various biocontrol techniques, tactics, and approaches. However, surveillance programs to monitor fungicide resistance and their environmental impact are much fewer compared to bacterial antibiotic resistance surveillance programs. In this review, we discuss the PPF that contributes to disease development in plants, the fungicides used against them, factors causing the spread of PPF and the emergence of new strains, the antifungal resistance mechanisms of PPF, health, the environmental impacts of fungicides, and the use of biocontrol agents (BCAs), antimicrobial peptides (AMPs), and nanotechnologies to control PPF as a safe and eco-friendly alternative to fungicides. Full article