Toxics最新文献

Chemical exposure in the environment can adversely affect the biodiversity of living organisms, particularly when persistent chemicals accumulate over time and disrupt the balance of microbial populations. In this study, we examined how chemical contaminants influence microorganisms in sediment and overlaying water samples collected from the Kinnickinnic, Milwaukee, and Menomonee Rivers near Milwaukee, Wisconsin, USA. We characterized these samples using shotgun metagenomic sequencing to assess microbiome diversity and employed chemical analyses to quantify more than 200 compounds spanning 16 broad classes, including pesticides, industrial products, personal care products, and pharmaceuticals. Integrative and differential comparative analyses of the combined datasets revealed that microbial density, approximated by adjusted total sequence reads, declined with increasing total chemical concentrations. Protozoan, metazoan, and fungal populations were negatively correlated with higher chemical concentrations, whereas certain bacterial (particularly Proteobacteria) and archaeal populations showed positive correlations. As expected, sediment samples exhibited higher concentrations and a wider dynamic range of chemicals compared to water samples. Varying levels of chemical contamination appeared to shape the distribution of microbial taxa, with some bacterial, metazoan, and protozoan populations present only at certain sites or in specific sample types (sediment versus water). These findings suggest that microbial diversity may be linked to both the type and concentration of chemicals present. Additionally, this study demonstrates the potential roles of multiple microbial kingdoms in degrading environmental pollutants, emphasizing the metabolic versatility of bacteria and archaea in processing complex contaminants such as polyaromatic hydrocarbons and bisphenols. Through functional and resistance gene profiling, we observed that multi-kingdom microbial consortia-including bacteria, fungi, and protozoa-can contribute to bioremediation strategies and help restore ecological balance in contaminated ecosystems. This approach may also serve as a valuable proxy for assessing the types and levels of chemical pollutants, as well as their effects on biodiversity.

Ambient air pollution has been associated with gestational diabetes mellitus (GDM); however, evidence regarding trimester-specific effects from China remains limited. This case-control study study analyzed data from pregnant women who delivered in Wuhan, China, between 2017 and 2022 (164 GDM cases and 731 controls), integrating geographic information, air quality measurements, and maternal characteristics. Using Inverse Distance Weighting interpolation and Generalized Linear Mixed Models (GLMM), we assessed associations between air pollutant exposure and GDM across different gestational periods. Results indicated that NO₂ demonstrated the strongest association with GDM compared to other pollutants. Specifically, increased NO₂ exposure was consistently associated with higher GDM risk throughout pregnancy. PM_2.5 exposure showed significant associations during early and mid-pregnancy, while SO₂ exposure was significantly associated with GDM risk exclusively in early pregnancy. Sensitivity analyses stratified by urban maternity status and maternal age revealed the stability of the study's findings. These findings underscore the importance of reducing air pollution exposure during pregnancy and implementing targeted interventions for high-risk populations to prevent GDM development.

This study examines long-term trends in fine particulate matter (PM_2.5) composition and oxidative potential in Los Angeles based on data from the University of Southern California's Particle Instrumentation Unit, with chemical composition retrieved from the EPA's Air Quality System (AQS). While regulatory interventions have reduced PM_2.5 mass concentration and primary combustion-related components, our findings reveal a more complex toxicity pattern. From 2001 to 2008, the PM_2.5 oxidative potential, measured via the dithiothreitol (DTT) assay, declined from ~0.84 to ~0.16 nmol/min/m³ under stringent tailpipe controls. However, after this initial decline, PM_2.5 DTT stabilized and gradually increased from ~0.35 in 2012 to ~0.97 nmol/min/m³ by 2024, reflecting the growing influence of non-tailpipe emissions such as brake/tire wear. Metals, such as iron (Fe, ~150 ng/m³) and zinc (Zn, ~10 ng/m³), remained relatively stable as organic and elemental carbon (OC and EC) declined, resulting in non-tailpipe contributions dominating PM_2.5 toxicity. Although PM_2.5 mass concentrations were effectively reduced, the growing contribution of non-tailpipe emissions (e.g., brake/tire wear and secondary organic aerosols) underscores the limitations of mass-based standards and tailpipe-focused strategies. Our findings emphasize the need to broaden regulatory strategies, targeting emerging sources that shape PM_2.5 composition and toxicity and ensuring more improvements in public health outcomes.

Background: Previous epidemiological evidence regarding the associations between ambient air pollution and two major neurodegenerative diseases, Alzheimer's disease (AD) and Parkinson's disease (PD), remains inconclusive.

Objective: This study aimed to evaluate the associations between long-term and short-term exposure to PM_2.5 and PM₁₀ (i.e., particulate matter with an aerodynamic diameter of, or smaller than, 2.5 μm or 10 μm), nitrogen dioxide (NO₂), ozone, sulfur dioxide, and carbon monoxide and the risks of AD and PD.

Methods: A random-effects model was used to summarize individual effect estimates in the meta-analysis. A subgroup meta-analysis was further conducted to explore the potential sources of heterogeneity.

Results: In total, 42 eligible studies were included. For each 5 μg/m³ increase in long-term PM_2.5 exposure, the odds ratios (ORs) were 1.16 (95% CI: 1.04, 1.30; I² = 95%) and 1.10 (95% CI: 1.03, 1.17; I² = 95%) for AD and PD, respectively. For each 5 μg/m³ increase in short-term PM_2.5 exposure, the OR was 1.01 (95% CI: 1.002, 1.01; I² = 77%) for PD. For each 1 ppb increase in long-term NO₂ exposure, the OR was 1.01 (95% CI: 1.0002, 1.02; I² = 79%) for PD.

Conclusion: Ambient air pollution, particularly PM_2.5, may contribute to the increased risks of neurodegenerative diseases including AD and PD.

Streptococcus suis (S. suis) is a major swine pathogen throughout the world as well as an emerging zoonotic agent. Among the symptoms caused by S. suis, including septicemia, pneumonia, endo-carditis, arthritis, and meningitis, the latter is the most overlooked. In the present study, we explored the mechanism of action of berberine against S. suis meningitis by obtaining berberine-related action targets, porcine S. suis meningitis targets, and human S. suis meningitis targets from open databases. We constructed a protein-protein interaction (PPI) network by using the STRING database and employed Cytoscape 3.8.0 to screen for core targets. We performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses through DAVID. We identified 31 potential targets of berberine, of which Toll-like receptor 4 (TLR4), fibronectin 1 (FN1), superoxide dismutase (SOD1), and catalase (CAT) were the four most critical targets. GO analysis revealed the enrichment of terms related to the response to oxidative stress and the inflammatory response. KEGG analysis revealed the enrichment of the interleukin 17 (IL-17), phosphoinositide 3-kinase (PI3K)-Akt, TLR, tumor necrosis factor (TNF), and mitogen-activated protein kinase (MAPK) signaling pathways. In addition, the admetSAR results showed that berberine can cross the blood-brain barrier. The molecular docking results indicated key binding activity between TLR4-berberine and FN1-berberine. In summary, berberine protects against Streptococcus suis meningitis by regulating inflammatory response and oxidative stress in humans and pigs. Our study updates the current knowledge of the targets of S. suis meningitis to exploit new drugs in humans and pigs, to develop environmentally friendly and antibiotic-free animal-derived food products, and to improve the farming industry and economic development.

Branched polyethyleneimine (PEI), possessing different types of amines-e.g., primary, secondary, and tertiary-in the polymer chains are well known for their antibacterial properties and DNA condensing ability, affording substantial advantages in many biomedical uses, including gene therapy. However, because of PEI's toxicity, depending on the molecular weight, its widespread biomedical use is hindered. Therefore, in this study, PEIs with different molecular weights-i.e., 600, 1200, and 1800 g/mol-were modified with 1,3-propane sultone, undergoing a sulfobetainization reaction in a single step to attain a zwitterionic structure: sulfobetainized PEI (b-PEI). The sulfobetainization reaction was carried out twice to increase the zwitterionic repeating unit on PEI chains. The increasing number of SO₃^- groups on the PEI chains was confirmed by the increased peak intensities around 1160 and 1035 cm^-1 on the FT-IR spectrum, which are assigned to symmetric and asymmetric S=O peaks. The elemental analysis results for first- and second- betainization PEIs, abbreviated as b¹-PEI and b²-PEI, respectively, were revealedthe increased wt% of S confirming the successful multiple-sulfobetainization of the PEI chains. Thermal stability analyses of PEIs and their corresponding multiple-sulfobetainized forms showed that multiple-sulfobetainization reactions increased the thermal stability of bare PEI chains. PEIs with lower molecular weights exhibited more antimicrobial properties. As PEI is sulfobetainated, its antimicrobial properties can be further adjusted via sulfobetainization (once or twice), or by adjusting the corresponding solution pH, or by protonating them with different acids with different counter anions. The cell toxicity of PEI on L929 fibroblast cells was slightly increased by increasing the molecular weight of the PEI, but all forms of sulfobetainized PEIs were found to be safe (no toxicity), even at 1000 µg/mL concentrations.

The evaluation of air pollution is a critical concern due to its potential severe impacts on human health. Currently, vast quantities of data are collected at high frequencies, and researchers must navigate multiannual, multisite datasets trying to identify possible pollutant sources while addressing the presence of noise and sparse missing data. To address this challenge, multivariate data analysis is widely used with an increasing interest in neural networks and deep learning networks along with well-established chemometrics methods and receptor models. Here, we report a combined approach involving the Self-Organizing Map (SOM) algorithm, Hierarchical Clustering Analysis (HCA), and Positive Matrix Factorization (PMF) to disentangle multiannual, multisite data in a single elaboration without previously separating the sites and years. The approach proved to be valid, allowing us to detect the site peculiarities in terms of pollutant sources, the variation in pollutant profiles during years and the outliers, affording a reliable interpretation.

Organic pollutants like per- and polyfluoroalkyl substances (PFASs) exhibit persistence, bioaccumulation, resistance to degradation, and high toxicity, garnering significant attention from scholars worldwide. To better address and mitigate the environmental risks posed by PFASs, this paper employs bibliometric analysis to examine the literature on PFASs' concentrations collected in the Web of Science (WoS) database between 2019 and 2024. The results show that the overall trend of PFASs' pollution research is relatively stable and increasing. In addition, this study also summarizes the pollution status of traditional PFASs across different environmental media in typical freshwater basins. It analyzes PFASs' concentrations in surface water, sediment, and aquatic organisms, elucidating their distribution characteristics and potential sources. While perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) levels in water environments are declining annually, short-chain PFASs and their substitutes are emerging as primary pollutants. Short-chain PFASs are frequently detected in surface water, whereas long-chain PFASs tend to accumulate in sediments. In aquatic organisms, PFASs are more likely to concentrate in protein-rich organs and tissues. The environmental presence of PFASs is largely influenced by human activities, such as metal plating, fluoride industry development, and industrial wastewater discharge. Currently, the development of PFASs in China faces a complex dilemma, entangled by policy and legal constraints, industrial production demands, the production and use of new alternatives, and their regulation and restriction, creating a vicious cycle. Breaking this deadlock necessitates continuous and active scientific research on PFASs, particularly PFOS, with an emphasis on detailed investigations of environmental sources and sinks. Furthermore, ecological and health risk assessments were conducted using Risk Quotient (RQ) and Hazard Quotient (HQ) methods. Comprehensive comparison indicates that PFASs (such as PFOA) in the majority of freshwater basins are at a low-risk level (RQ < 0.1 or HQ < 0.2), PFOS in some freshwater basins is at a medium-risk level (0.1 < RQ < 1), and no freshwater basin is at a high-risk level. The adsorption and removal approaches of PFASs were also analyzed, revealing that the combination of multiple treatment technologies as a novel integrated treatment technology holds excellent prospects for the removal of PFASs.

Firefighters are occupationally exposed to many chemicals, including polycyclic aromatic hydrocarbons (PAHs), which are formed by the incomplete combustion of organic matter during fire response and training activities. However, due to the harsh environments in which firefighters work, as well as consideration for time and physical safety while wearing bulky equipment, traditional active sampling methods may not be feasible to measure PAH exposures. Silicone passive samplers offer an alternative approach to assess exposure during fire responses and live fire training due to their heat resistance and ease of deployment in remote or time-limited environments. In this study, the primary objective was to investigate and determine the statistical strength of the relationship between active air sampling methods and passive silicone samplers for PAHs. In this study, silicone wristbands were paired with active sampling devices in a series of burn experiments to compare PAH measurements. Silicone-based measurements correlated strongly with active air samples for the dominant PAHs found, naphthalene and phenanthrene; however, detection was limited in the wristbands when air concentrations were low in active samples. In situations where PAH levels are expected to be high and the potential for contaminant loss via off-gassing is low, silicone samplers may be a useful tool for industrial hygienists to measure PAHs in fire and other emergency responses in extreme environments.

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals widely used in consumer and industrial products due to their unique physicochemical properties. However, their persistence and bioaccumulative potential pose significant environmental and human health risks. This review focuses on the use of non-invasive matrices-urine, hair, and nails-for the human biomonitoring of PFAS, highlighting key findings from scientific studies. While urine offers a non-invasive and practical option, its limited sensitivity for long-chain PFAS requires further analytical advances. Hair and nails have demonstrated potential for use in biomonitoring, with higher detection frequencies and concentrations for certain PFAS compared to urine. The variability in PFAS levels across studies reflects differences in population characteristics, exposure sources, and geographic regions. This review emphasizes the need for standardized analytical methods, expanded population studies, and the use of complementary matrices to enhance the accuracy and reliability of PFAS exposure assessment.