Search Results (348)

Environmental DNA (eDNA) analysis has emerged as a transformative tool in environmental monitoring, enabling non-invasive detection of species and microbial communities across diverse ecosystems. This study systematically reviews the role of bioinformation technology in eDNA analysis, focusing on methodologies and applications across air, soil, groundwater, sediment, and aquatic environments. Advances in molecular biology, high-throughput sequencing, bioinformatics tools, and field-deployable detection systems have significantly improved eDNA detection sensitivity, allowing for early identification of invasive species, monitoring ecosystem health, and tracking pollutant degradation processes. Airborne eDNA monitoring has demonstrated potential for assessing microbial shifts due to air pollution and tracking pathogen transmission. In terrestrial environments, eDNA facilitates soil and groundwater pollution assessments and enhances understanding of biodegradation processes. In aquatic ecosystems, eDNA serves as a powerful tool for biodiversity assessment, invasive species monitoring, and wastewater-based epidemiology. Despite its growing applicability, challenges remain, including DNA degradation, contamination risks, and standardization of sampling protocols. Future research should focus on integrating eDNA data with remote sensing, machine learning, and ecological modeling to enhance predictive environmental monitoring frameworks. As technological advancements continue, eDNA-based approaches are poised to revolutionize environmental assessment, conservation strategies, and public health surveillance. Full article

Combustion of aviation jet fuel emits a complex mixture of pollutants linked to adverse health outcomes among airport personnel and nearby communities. While epidemiological studies showed the detrimental effects of aviation-derived air pollutants on human health, the molecular mechanisms of the interactions of these pollutants with cellular biomolecules like proteins that drive the adverse health effects remain poorly understood. In this study, we performed molecular docking simulations of 272 pollutant–protein complexes using AutoDock Vina 1.2.7 to characterize the binding strength of the pollutants with the selected proteins. We selected 34 aviation-derived pollutants that constitute three chemical categories of pollutants: volatile organic compounds (VOCs), polyaromatic hydrocarbons (PAHs), and organophosphate esters (OPEs). Each pollutant was docked to eight proteins that play critical roles in endocrine, metabolic, transport, and neurophysiological functions, where functional disruption is implicated in disease. The effect of binding of multiple pollutants was analyzed. Our results indicate that aliphatic and monoaromatic VOCs display low (<6 kcal/mol) binding affinities while PAHs and organophosphate esters exhibit strong (>7 kcal/mol) binding affinities. Furthermore, the binding strength of PAHs exhibits a positive correlation with the increasing number of aromatic rings in the pollutants, ranging from nearly 7 kcal/mol for two aromatic rings to more than 15 kcal/mol for five aromatic rings. Analysis of intermolecular interactions showed that these interactions are predominantly stabilized by hydrophobic, pi-stacking, and hydrogen bonding interactions. Simultaneous docking of multiple pollutants revealed the increased binding strength of the resulting complexes, highlighting the detrimental effect of exposure to pollutant mixtures found in ambient air near airports. We provide a priority list of pollutants that regulatory authorities can use to further develop targeted mitigation strategies to protect the vulnerable personnel and communities near airports. Full article

Antimicrobial resistance (AMR) has emerged as a planetary health emergency, driven not only by the clinical misuse of antibiotics but also by diverse environmental dissemination pathways. This review critically examines the role of environmental compartments—water, soil, and air—as dynamic reservoirs and transmission routes for antibiotic-resistant bacteria (ARB) and resistance genes (ARGs). Recent metagenomic, epidemiological, and mechanistic evidence demonstrates that anthropogenic pressures—including pharmaceutical effluents, agricultural runoff, untreated sewage, and airborne emissions—amplify resistance evolution and interspecies gene transfer via horizontal gene transfer mechanisms, biofilms, and mobile genetic elements. Importantly, it is not only highly polluted rivers such as the Ganges that contribute to the spread of AMR; even low concentrations of antibiotics and their metabolites, formed during or after treatment, can significantly promote the selection and dissemination of resistance. Environmental hotspots such as European agricultural soils and airborne particulate zones near wastewater treatment plants further illustrate the complexity and global scope of pollution-driven AMR. The synergistic roles of co-selective agents, including heavy metals, disinfectants, and microplastics, are highlighted for their impact in exacerbating resistance gene propagation across ecological and geographical boundaries. The efficacy and limitations of current mitigation strategies, including advanced wastewater treatments, thermophilic composting, biosensor-based surveillance, and emerging regulatory frameworks, are evaluated. By integrating a One Health perspective, this review underscores the imperative of including environmental considerations in global AMR containment policies and proposes a multidisciplinary roadmap to mitigate resistance spread across interconnected human, animal, and environmental domains. Full article

Introduction: Air pollution is a risk factor for a variety of cardiopulmonary diseases and is a contributing factor to cancer, diabetes, and cognitive impairment. The impact on mortality is not clearly elucidated. Objectives: The goal of this study is to determine the impact (if any) of air pollution on the 5-year mortality of patients in the American Family Cohort (AFC) dataset. Methods: The AFC dataset is derived from the American Board of Family Medicine PRIME Registry electronic health record data. It includes longitudinal information from 6.6 million unique patients from an estimated 800 primary care practices across 47 states, with 40% coming from rural areas. The Environmental Protection Agency’s Air Quality Index (AQI) measures were downloaded for the study period (2016–2022). Using the Python library pandas, the AFC and EPA datasets were merged with respect to date, time, and location. Cox Regression Models were performed on the merged dataset to determine the impact (if any) of air quality on patients’ five-year survival. In the model, AQI was handled as a time-independent (time-fixed) covariate. Results: The group with AQI > 50 had an adjusted hazard of death that was 4.02 times higher than the hazard of death in the group with AQI ≤ 50 (95% CI: 3.36, 4.82, p < 0.05). The hazard of death was 6.73 times higher in persons older than 80 years of age (95% CI: 5.47, 8.28; p < 0.05) compared to those younger than 80 years of age. Black/African American patients had a 4.27 times higher hazard of death (95%CI: 3.47, 5.26; p < 0.05) compared to other races. We also found that regional effects played a role in survival. Conclusions: Poor air quality was associated with a higher hazard of mortality, and this phenomenon was particularly pronounced in Black/African American patients and patients older than 80 years of age. Air pollution is an important social determinant of health. Public health initiatives that improve air quality are necessary to improve health outcomes. Full article

Climate change and air pollution are reshaping viral circulation patterns and increasing host vulnerability, amplifying the burden of respiratory illness in early childhood. This narrative review synthesizes current evidence on how environmental exposures, particularly to nitrogen dioxide, ozone, and fine particulate matter, contribute to the incidence and severity of bronchiolitis, with a focus on biological mechanisms, epidemiological trends, and public health implications. Bronchiolitis remains one of the leading causes of hospitalization in infancy, with Respiratory Syncytial Virus (RSV) being responsible for the majority of severe cases. Airborne pollutants penetrate deep into the airways, triggering inflammation, compromising mucosal defenses, and impairing immune function, especially in infants with pre-existing vulnerabilities. These interactions can intensify the clinical course of viral infections and contribute to more severe disease presentations. Children in urban areas exposed to high levels of traffic-related emissions are disproportionately affected, underscoring the need for integrated public health interventions. These include stricter emission controls, urban design strategies to reduce exposure, and real-time health alerts during pollution peaks. Prevention strategies should also address indoor air quality and promote risk awareness among families and caregivers. Further research is needed to standardize exposure assessments, clarify dose–response relationships, and deepen our understanding of how pollution interacts with viral immunity. Bronchiolitis emerges as a sentinel condition at the crossroads of climate, environment, and pediatric health, highlighting the urgent need for collaboration across clinical medicine, epidemiology, and environmental science. Full article

Air pollution is a known contributor to cancer risk, although its specific impact on endometrial cancer (EC) remains unclear. This study integrates network toxicology, transcriptomics, molecular docking, and machine learning to investigate pollutant–gene interactions in EC. We identify 83 air pollution-associated EC genes (APECGs), with TNF, ESR1, IL1B, NFKB1, and PTGS2 as the hub genes. A 13-gene RSF-SuperPC model, including CCNE1, SLC2A1, AHCY, and CDC25C, shows effective prognostic stratification. Molecular docking reveals strong binding between pollutants (e.g., benzene, toluene, and ethylbenzene) and key APECGs. The enrichment and SHAP analyses suggest that pollutant-driven EC progression involves DNA damage, metabolic reprogramming, epigenetic dysregulation, immune suppression, and inflammation. These findings reveal potential mechanisms linking air pollution to EC and support the development of biomarkers for high-exposure populations. Further experimental and epidemiological validation is needed to enable clinical translation. Full article

Background: Hand, foot, and mouth disease (HFMD) typically exhibits spatiotemporal clustering. This study aimed to analyze the spatiotemporal heterogeneity of HFMD in Fujian Province, China, and to identify the associations of air pollutants and socioeconomic factors with the incidence. Methods: Daily reported HFMD case data, daily air pollutant data, and socioeconomic data in Fujian Province from 2014 to 2023 were collected for analysis. A descriptive analysis was used to describe the epidemiological trends of HFMD. Spatial autocorrelation analysis was applied to explore the spatiotemporal clustering characteristics. The associations between risk factors and HFMD incidence were evaluated using the generalized additive model (GAM). Results: HFMD incidence in Fujian has decreased since 2019, and the peak in each year occurred between May and June. Distinct high–high and low–low clustering areas were identified. The cumulative exposure–response curves for SO₂, NO₂, and CO showed a monotonically increasing trend, with relative risks (RRs) < 1 at concentrations lower than the median levels (SO₂ ≈ 4 μg/m³, NO₂ ≈ 16 μg/m³, CO ≈ 1 mg/m³). In contrast, the curves for O₃ and PM_2.5 showed a decreasing trend, with RR < 1 at concentrations above the median levels (O₃ ≈ 55 μg/m³, PM_2.5 ≈ 20 μg/m³). Among socioeconomic factors, only the proportion of the population under 15 years old was found to be associated with HFMD incidence. Conclusions: HFMD incidence in Fujian exhibited distinct spatiotemporal clustering. The incidence was associated with the concentrations of air pollutants. Targeted interventions should be implemented in high-risk areas to mitigate HFMD transmission, with particular attention given to the environmental and demographic factors. Full article

This study investigates the combined effects of air pollution and socioeconomic factors on disease incidence and severity, addressing gaps in prior research that often analyzed these factors separately. Using data from 86,170 hospitalizations in Mexico City (2015–2019), we employed multivariate statistical methods (PCA and factor analysis) to construct composite measures of social and economic status and grouped correlated pollutants. Logistic and negative binomial regression models assessed their associations with hospitalization risk and frequency. Results showed that economic status significantly influenced diabetes complications, while social factors affected prenatal care-related diseases and hypertension. The ${\mathrm{PM}}_{10}$–${\mathrm{PM}}_{2.5}$–CO group increased the incidence of asthma, influenza, and epilepsy, whereas ${\mathrm{NO}}_2$–${\mathrm{NO}}_x$ impacted diabetes complication severity and influenza. Nonlinear effects and interactions (e.g., age and weight) were also identified, highlighting the need for integrated analyses in environmental health research. Full article

Atmospheric air pollution is a major environmental and public health concern, particularly in industrialized regions. The East Kazakhstan Region exhibits high rates of oncological, cardiovascular, and respiratory diseases. However, the specific impact of industrial emissions on morbidity remains insufficiently studied. This study employed correlation and regression analyses using data on pollutant emissions and population morbidity indicators from 2014 to 2023. Correlation and regression methods, along with geoinformation technologies, were applied. A moderate positive correlation was found between industrial emission volumes and the incidence of neoplasms (r = 0.59, R² = 0.35), especially in areas with high concentrations of sulfur dioxide, nitrogen oxides, and particulate matter. The findings confirm the significant influence of polluted air—particularly mixed pollutants—on the increase in cancer-related diseases. The conclusions emphasize the urgent need to implement emission reduction measures, enhance environmental monitoring and disease prevention, and carry out further epidemiological research. Full article

Tyre wear particles (TWPs), generated from tyre-road abrasion, are a pervasive and under-regulated environmental pollutant, accounting for a significant share of global microplastic contamination. Recent estimates indicate that 1.3 million metric tons of TWPs are released annually in Europe, dispersing via atmospheric transport, stormwater runoff, and sedimentation to contaminate air, water, and soil. TWPs are composed of synthetic rubber polymers, reinforcing fillers, and chemical additives, including heavy metals such as zinc (Zn) and copper (Cu) and organic compounds like polycyclic aromatic hydrocarbons (PAHs) and N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD). These constituents confer persistence and bioaccumulative potential. While TWP toxicity in aquatic systems is well-documented, its ecological impacts on terrestrial environments, particularly in agricultural soils, remain less understood despite global soil loading rates exceeding 6.1 million metric tons annually. This review synthesizes global research on TWP sources, environmental fate, and ecotoxicological effects, with a focus on soil–plant systems. TWPs have been shown to alter key soil properties, including a 25% reduction in porosity and a 20–35% decrease in organic matter decomposition, disrupt microbial communities (with a 40–60% reduction in nitrogen-fixing bacteria), and induce phytotoxicity through both physical blockage of roots and Zn-induced oxidative stress. Human exposure occurs through inhalation (estimated at 3200 particles per day in urban areas), ingestion, and dermal contact, with epidemiological evidence linking TWPs to increased risks of respiratory, cardiovascular, and developmental disorders. Emerging remediation strategies are critically evaluated across three tiers: (1) source reduction using advanced tyre materials (up to 40% wear reduction in laboratory tests); (2) environmental interception through bioengineered filtration systems (60–80% capture efficiency in pilot trials); and (3) contaminant degradation via novel bioremediation techniques (up to 85% removal in recent studies). Key research gaps remain, including the need for long-term field studies, standardized mitigation protocols, and integrated risk assessments. This review emphasizes the importance of interdisciplinary collaboration in addressing TWP pollution and offers guidance on sustainable solutions to protect ecosystems and public health through science-driven policy recommendations. Full article

Ambient fine particulate matter of size less than 2.5 μm in aerodynamic diameter (PM_2.5) is a key ambient air pollutant that has been linked to numerous adverse health outcomes. Reliable estimates of PM_2.5 are important for supporting epidemiological and health impact assessment studies. Precise measurements of PM_2.5 are available through networks of monitors; however, these are spatially sparse and temporally incomplete. Chemical transport model (CTM) simulations and satellite-retrieved aerosol optical depth (AOD) measurements are two data sources that have been used to develop prediction models for PM_2.5 at fine spatial resolutions with increased spatial coverage. As part of the Multi-Angle Imager for Aerosols (MAIA) project, a geostatistical regression model has been developed to bias-correct AOD, followed by Bayesian ensemble averaging to gap-fill missing AOD values with CTM simulations. Here, we present a suite of statistical software (available in the R package ensembleDownscaleR) to facilitate the adaptation of this modeling approach to other settings and air quality modeling applications. We describe the Bayesian ensemble averaging approach, model specifications, estimation methods, and evaluation via cross-validation that is implemented in the software. We also provide a case study of estimating PM_2.5 using 2018 data from the Los Angeles metropolitan area with an accompanying tutorial. All code is fully reproducible and available on GitHub, data are made on Zenodo, and the ensembleDownscaleR package is available for download on GitHub. Full article

Several epidemiological studies have documented associations between air pollution exposure and cardiovascular responses, including adverse effects of air pollutants on blood pressure (BP). However, previous studies only considered the effect of specific air pollutants on resting BP, and did not sufficiently consider the independent effects of various air pollution species as well as their overall mixture effect. We addressed this gap in our MobiliSense sensor-based study among 273 participants living in the Grand Paris region. Participants wore personal monitors to assess personal exposure to particles [black carbon and particulate matter smaller than 2.5 μm in diameter (PM_2.5)] and gaseous pollutants [ozone (O₃), nitrogen monoxide (NO), carbon monoxide (CO), and nitrogen dioxide (NO₂)] along with noise exposure. Participants were asked to measure their blood pressure (BP) at rest in the mornings and evenings for three days. Multilevel models with a random intercept at the individual level explored the relationship between air pollution exposure (averaged over the day) and change in resting BP from morning to evening. We also used the quantile G-computation method to estimate the joint effect of the mixture of targeted air pollutants on resting BP. Sensitivity analyses examined the associations between air pollution exposure averaged at different temporal scales before evening BP measurements and the outcome. A quantile increase in the mixture of air pollutants (PM_2.5, NO₂, NO, CO, and O₃) over the day did not affect changes in systolic BP [−0.33 mmHg (95% CI: −3.31, 2.65)] and diastolic BP [−0.53 mmHg (95% CI: −2.66, 1.60)] from morning to evening. When shorter time exposure windows were considered (from a few minutes to a few hours), both NO and the mixture showed positive associations with the morning-to-evening DBP change in only some of the models. Future studies with sufficient repeated BP measurements for more participants should test the association at varying temporal scales (minutes to days) to better understand how air pollution exposure influences resting BP. Full article

Asthma is a chronic inflammatory disease characterized by airway hyperresponsiveness, variable airflow obstruction, and persistent inflammation. While its pathophysiology is well established, growing evidence highlights significant sex-based differences in its prevalence, severity, and treatment response. Epidemiological studies indicate that asthma is more common in prepubertal boys but shifts toward a female predominance after puberty, with adult women experiencing higher morbidity and greater healthcare utilization. These disparities suggest a crucial role for sex hormones, genetic predisposition, and epigenetic regulation in asthma pathogenesis. Sex hormones modulate immune responses, contributing to disease progression. Estrogen enhances type 2 inflammation, increases eosinophilic infiltration, and upregulates IL-4 and IL-13 expression, leading to greater airway hyperreactivity in women. Additionally, progesterone fluctuations correlate with perimenstrual asthma exacerbations, while testosterone appears to exert a protective effect by dampening Th2-driven inflammation and airway remodeling. These hormonal influences contribute to sex-specific asthma phenotypes and treatment responses. Genetic and epigenetic factors further shape sex-related differences in asthma. The X chromosome harbors immune-regulatory genes, including TLR7 and TLR8, which amplify inflammatory responses in females. The sex-dependent expression of IL13 and ORMDL3 influences eosinophilic inflammation and airway remodeling. Epigenetic modifications, such as DNA methylation and microRNA regulation, further impact immune activation and corticosteroid responsiveness. For instance, Let-7 miRNAs modulate IL-13 expression, contributing to sex-specific inflammatory profiles. Environmental factors, including air pollution, obesity, and diet, interact with hormonal and genetic influences, exacerbating sex disparities in asthma severity. Obesity-related metabolic dysfunction promotes systemic inflammation, airway remodeling, and steroid resistance, disproportionately affecting women. Given these complex interactions, sex-specific approaches to asthma management are essential. Personalized treatment strategies targeting hormonal pathways, immune regulation, and metabolic health may improve outcomes for both men and women with asthma. Future research should focus on sex-based therapeutic interventions to optimize disease control and mitigate healthcare disparities. Full article

Background: Ambient air pollution is a modifiable determinant of lung cancer survival, affecting early-stage Non-Small Cell Lung Cancer (NSCLC) incidence and mortality. Methods: This retrospective cohort study examined the association between all-cause mortality and exposure to air pollution among stage 1A NSCLC-treated patients from the U.S. National Cancer Registry from 1988 to 2015. The Cox hazard model and Kaplan–Meier survival plots were provided. Air pollutants were included separately and together in the models, accounting for spatiotemporal weather variability affecting air pollution exposure levels pre and post lung cancer diagnosis. Results: NO₂ (above the median sample mean = 25.66 ppb; 12.97 ppb below median), SO₂ (above median sample mean = 3.98 ppb; 1.81 ppb below median), and CO (above median sample mean = 1010.84 ppb; 447.91 ppb below median) air pollutant levels and weather conditions were calculated for county-day units. The median months of survival for those exposed to above-median NO₂ were 27 months (SD = 17.61 months), while the median was 30 months (SD = 15.93 months) for those exposed to below-median levels. Multipollutant analyses indicated that an average monthly NO₂ increase of 1 part per billion (ppb) in the county of NSCLC diagnosis was associated with increases of 4%, 6%, and 9% in the all-cause mortality rate one, three, and five years after diagnosis, respectively; an equivalent increase in SO₂ was associated with increases of 16%, 17%, and 17%; and an increase in CO was associated with increases of 53%, 51%, and 42% Conclusion: It is vital to implement environmental policies that control emissions to reduce preventable deaths in stage 1A NSCLC patients with adenocarcinoma or squamous cell carcinoma histology types who reside in metropolitan areas. Full article

Even at historically low levels of air pollution, epidemiological time series studies carried out in cities across the globe have documented its substantial detrimental health effects. A time series analysis of counts of respiratory hospital admissions in Gjakova and outdoor air pollutants was performed, applying a General Additive Model with a Poisson distribution, controlling for time trends and meteorological factors over a 4-year period (2020–2023) with different time lags (0–7 days). The effects were further analyzed per age group (children and adults). We found significant associations between gaseous pollutants, mainly NO₂, and respiratory disease-related hospital admissions in the city. The strongest association between NO₂ and total hospital admissions was observed after a lag of 6 days, with an increase of 0.14 cases per 10 μg/m³ increase in concentration. The effects were stronger in adults. An adverse effect was also seen with SO₂, but not particulate pollution. Our findings call for greater awareness regarding environmental protection and the implementation of effective measures to improve air quality, which may reduce the risk of adverse health effects. Full article