Search Results (460)

Perfluoroalkyl substances (PFASs) possess immunosuppressive properties. However, their association with rheumatoid arthritis (RA) risk remains inconclusive across epidemiological studies. This study integrates population-based and mechanistic evidence to clarify the relationship between PFAS exposure and RA. We analyzed 8743 U.S. adults from the NHANES (2005–2018), assessing individual and mixed exposures to PFOA, PFOS, PFNA, and PFHxS using multivariable logistic regression, Bayesian kernel machine regression, quantile g-computation, and weighted quantile sum models. Network toxicology and molecular docking were utilized to identify core targets mediating immune disruption. The results showed that elevated PFOA (OR = 1.63, 95% CI: 1.41–1.89), PFOS (OR = 1.41, 1.25–1.58), and PFNA (OR = 1.40, 1.20–1.63) levels significantly increased RA risk. Mixture analyses indicated a positive joint effect (WQS OR = 1.06, 1.02–1.10; qgcomp OR = 1.26, 1.16–1.38), with PFOA as the primary contributor. Stratified analyses revealed stronger effects in females (PFOA Q4 OR = 3.75, 2.36–5.97) and older adults (≥60 years). Core targets included EGFR, SRC, TP53, and CTNNB1. PFAS mixtures increase RA risk, dominated by PFOA and modulated by sex/age. These findings help reconcile prior contradictions by identifying key molecular targets and vulnerable subpopulations, supporting regulatory attention to PFAS mixture exposure. Full article

Modern agriculture relies heavily on the use of pesticides, with one-third of them being herbicides. Chloroacetamides are the most widely used herbicides because of their high effectiveness, but their extensive use poses environmental challenges and threatens the health of living organisms due to toxicity risks. Since the pharmacokinetic behavior and toxicity of a compound are influenced by its lipophilicity, this essential physicochemical parameter for disubstituted chloroacetamides was determined in silico and experimentally through thin-layer chromatography on reversed phases (RPTLC C18/UV254s) in mixtures of water and distinct organic modifiers. The pharmacokinetic profile of chloroacetamides was analyzed by using the BOILED-Egg model. The correlation between the obtained chromatographic parameters and software-based lipophilicity, pharmacokinetic, and ecotoxicity predictors of the studied chloroacetamides was assessed by using linear regression, but more comprehensive insight was obtained through multivariate methods—Cluster Analysis and Principal Component Analysis. It was observed that the total number of carbon atoms in the structure of their molecules, along with the type of hydrocarbon substituents, are the most important factors affecting lipophilicity, pharmacokinetics, and potential toxicity to non-target organisms. Full article

The aviation industry is under increasing pressure to reduce its environmental impact while maintaining safety and performance standards. One promising area for improvement lies in the use of sustainable materials in airport infrastructure. One of the issues preventing uptake of emerging sustainable technologies is the lack of guidance relating to the opportunities, potential benefits, associated risks and an implementation plan specific to airport pavements. This research reviewed opportunities to incorporate waste materials into rigid airport pavements, focusing on concrete base slabs. Commonly used supplementary cementitious materials (SCMs), such as fly ash and ground granulated blast furnace slag (GGBFS) were considered, as well as recycled aggregates, including recycled concrete aggregate (RCA), recycled crushed glass (RCG), and blast furnace slag (BFS). Environmental Product Declarations (EPDs) were also used to quantify the potential for environmental benefit associated with various concrete mixtures, with findings showing 23% to 50% reductions in embodied carbon are possible for selected theoretical concrete mixtures that incorporate waste materials. With considered evaluation and structured implementation, the integration of waste materials into rigid airport pavements offers a practical and effective route to improve environmental outcomes in aviation infrastructure. It was concluded that a Triple Bottom Line (TBL) framework—assessing financial, environmental, and social factors—guides material selection and can support sustainable decision-making, as does performance-based specifications that enable sustainable technologies to be incorporated into airport pavement. The study also proposed a consequence-based implementation hierarchy to facilitate responsible adoption of waste materials in airside pavements. The outcomes of this review will assist airport managers and pavement designers to implement practical changes to achieve more sustainable rigid airport pavements in the future. Full article

Background: Environmental exposures, such as per- and polyfluoroalkyl substances (PFAS), in conjunction with social and behavioral factors, can significantly impact liver health. This research investigates the combined effects of PFAS (perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), alcohol consumption, smoking, income, and education on liver function among the U.S. population, utilizing data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES). Methods: PFAS concentrations in blood samples were analyzed using online solid-phase extraction combined with liquid chromatography–tandem mass spectrometry (LC-MS/MS), a highly sensitive and specific method for detecting levels of PFAS. Liver function was evaluated using biomarkers such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), total bilirubin, and the fatty liver index (FLI). Descriptive statistics and multivariable linear regression analyses were employed to assess the associations between exposures and liver outcomes. Bayesian Kernel Machine Regression (BKMR) was utilized to explore the nonlinear and interactive effects of these exposures. To determine the relative influence of each factor on liver health, Posterior Inclusion Probabilities (PIPs) were calculated. Results: Linear regression analyses indicated that income and education were inversely associated with several liver injury biomarkers, while alcohol use and smoking demonstrated stronger and more consistent associations. Bayesian Kernel Machine Regression (BKMR) further highlighted alcohol and smoking as the most influential predictors, particularly for GGT and total bilirubin, with posterior inclusion probabilities (PIPs) close to 1.0. In contrast, PFAS showed weaker associations. Regression coefficients were small and largely non-significant, and PIPs were comparatively lower across most liver outcomes. Notably, education had a higher PIP for ALT and GGT than PFAS, suggesting a more protective role in liver health. People with higher education levels tend to live healthier lifestyles, have better access to healthcare, and are generally more aware of health risks. These factors can all help reduce the risk of liver problems. Overall mixture effects demonstrated nonlinear trends, including U-shaped relationships for ALT and GGT, and inverse associations for AST, FLI, and ALP. Conclusion: These findings underscore the importance of considering both environmental and social–behavioral determinants in liver health. While PFAS exposures remain a long-term concern, modifiable lifestyle and structural factors, particularly alcohol, smoking, income, and education, exert more immediate and pronounced effects on hepatic biomarkers in the general population. Full article

Food safety concerns related to pesticide residues in fruits and vegetables have increased globally, particularly in regions where monitoring programs are scarce or inconsistent. This study provides the first multi-year evaluation of pesticide contamination and associated dietary risks in Cape Verde, an African island nation increasingly reliant on imported produce. A total of 570 samples of fruits and vegetables—both locally produced and imported—were collected from major markets across the country between 2017 and 2020 and analyzed using validated multiresidue methods based on gas chromatography coupled to Ion Trap mass spectrometry (GC-IT-MS/MS), and both gas and liquid chromatography coupled to triple quadrupole tandem mass spectrometry (GC-QqQ-MS/MS and LC-QqQ-MS/MS). Residues were detected in 63.9% of fruits and 13.2% of vegetables, with imported fruits showing the highest contamination levels and diversity of compounds. Although only one sample exceeded the maximum residue limits (MRLs) set by the European Union, 80 different active substances were quantified—many of them not authorized under the current EU pesticide residue legislation. Dietary exposure was estimated using median residue levels and real consumption data from the national nutrition survey (ENCAVE 2019), enabling a refined risk assessment based on actual consumption patterns. The cumulative hazard index for the adult population was 0.416, below the toxicological threshold of concern. However, when adjusted for children aged 6–11 years—taking into account body weight and relative consumption—the cumulative index approached 1.0, suggesting a potential health risk for this vulnerable group. A limited number of compounds, including omethoate, oxamyl, imazalil, and dithiocarbamates, accounted for most of the risk. Many are banned or heavily restricted in the EU, highlighting regulatory asymmetries in global food trade. These findings underscore the urgent need for strengthened residue monitoring in Cape Verde, particularly for imported products, and support the adoption of risk-based food safety policies that consider population-specific vulnerabilities and mixture effects. The methodological framework used here can serve as a model for other low-resource countries seeking to integrate analytical data with dietary exposure in a One Health context. Full article

Mycotoxins are toxic secondary metabolites produced by various fungi that contaminate livestock feed, posing serious threats to animal health, productivity, and food safety. Although historical research has often examined individual mycotoxins in isolation, real-world conditions typically involve the simultaneous presence of multiple mycotoxins, resulting in additive or synergistic toxic effects that are often more severe than those observed with single toxin exposures. This review comprehensively synthesizes recent findings on multi-mycotoxin contamination in livestock feed, highlighting their physiological effects, mechanisms of action, and implications for regulatory frameworks. Multi-mycotoxin interactions exacerbate oxidative stress, immune suppression, impaired reproduction, and organ damage across species, leading to reduced growth performance, decreased milk and egg production, compromised carcass and wool quality, and increased mortality rates. A major concern is that current international regulatory standards mainly address individual mycotoxins, overlooking the compounded risks of co-occurrence. Global surveillance studies consistently reveal high prevalence rates of mycotoxin mixtures in feedstuffs, especially combinations involving DON, ZEN, AFB₁, FB₁, and OTA. Understanding these interactions and their underlying cellular mechanisms is critical for improving risk assessment models, formulating integrated mitigation strategies, and safeguarding both livestock productivity and human food security. Full article

Background: Pharmaceutical compounds frequently co-occur in environmental waters, but studies on their combined effects on animals and humans remain limited. The present study investigated the individual and combined short-term effects of ketoprofen (Kp, a nonsteroidal anti-inflammatory drug inhibiting cyclooxygenase-2), valproic acid (VPA, an anticonvulsant acting as a voltage-gated sodium channel modulator), and meropenem (Mp, a β-lactam antibiotic) at environmentally relevant concentrations on zebrafish behavior, acetylcholinesterase (AChE) activity, and oxidative status. Methods: Adult zebrafish were exposed for 4 days to Kp, VPA, Mp, and their binary and ternary mixtures. Behavioral effects were assessed using 3D novel tank and social behavior tests, while the oxidative stress response was assessed through malondialdehyde (MDA) content, superoxide dismutase (SOD), and glutathione peroxidase (GPx) activities. Results: Zebrafish exposed to Mp showed a notable increase in immobility, whereas those exposed to VPA and Mp + Kp exhibited a significant augmentation of average velocity and counter-clockwise rotations. All treated groups exhibited a notable increase in the time spent near the walls (thigmotaxis), and except for the control and Mp-exposed zebrafish, the other groups mostly stayed in the bottom tank zone (geotaxis). Kp, VPA + Kp, and VPA + Mp + Kp treatments impaired social behavior, with zebrafish displaying less interest in conspecifics. Biochemical analysis demonstrated that both the individual drugs and their combination caused oxidative stress, characterized by decreased GPx activity and increased SOD activity and MDA levels. Moreover, AChE activity was more strongly inhibited in zebrafish exposed to the binary and ternary mixtures than to individual drugs. Conclusions: The results indicate that acute exposure to individual and/or combined pharmaceuticals induces behavioral changes, oxidative damage, and AChE inhibition in zebrafish, highlighting the need to assess the effects of pharmaceutical mixtures for comprehensive ecosystem risks evaluation. Full article

Slope stability analysis is conventionally performed using the strength reduction method with the proportional reduction in shear strength parameters. However, during actual slope failure processes, the attenuation characteristics of rock mass cohesion ($c$) and internal friction angle ($\phi$) are often inconsistent, and their reduction paths exhibit clear nonlinearity. Relying solely on proportional reduction paths to calculate safety factors may therefore lack scientific rigor and fail to reflect true slope behavior. To address this limitation, this study proposes a novel approach that considers the non-proportional reduction of $c$ and $\phi$, without dependence on predefined reduction paths. The method begins with an analysis of slope stability states based on energy dissipation theory. A Bayesian Gaussian Mixture Model (BGMM) is employed for intelligent interpretation of the dissipated energy data, and, combined with energy mutation theory, is used to identify instability states under various reduction parameter combinations. To compute the safety factor, the concept of a “reference slope” is introduced. This reference slope represents the state at which the slope reaches limit equilibrium under strength reduction. The safety factor is then defined as the ratio of the shear strength of the target analyzed slope to that of the reference slope, providing a physically meaningful and interpretable safety index. Compared with traditional proportional reduction methods, the proposed approach offers more accurate estimation of safety factors, demonstrates superior sensitivity in identifying critical slopes, and significantly improves the reliability and precision of slope stability assessments. These advantages contribute to enhanced safety management and risk control in slope engineering practice. Full article

Steel corrosion prediction in concrete infrastructure remains a critical challenge for durability assessment and maintenance planning. This study presents a comprehensive framework integrating domain expertise with advanced machine learning for carbonation-induced corrosion prediction. Four Gaussian Process Regression (GPR) variants were systematically developed: Baseline GPR with manual optimization, Expert Knowledge GPR employing domain-driven dual-kernel architecture, GPR with Automatic Relevance Determination (GPR-ARD) for feature selection, and GPR-OptCorrosion featuring specialized multi-component composite kernels. The models were trained and validated using 180 carbonated mortar specimens with 15 systematically categorized variables spanning mixture, material, environmental, and electrochemical parameters. GPR-OptCorrosion achieved superior performance (R² = 0.9820, RMSE = 1.3311 μA/cm²), representing 44.7% relative improvement in explained variance over baseline methods, while Expert Knowledge GPR and GPR-ARD demonstrated comparable performance (R² = 0.9636 and 0.9810, respectively). Contrary to conventional approaches emphasizing electrochemical indicators, automatic relevance determination revealed supplementary cementitious materials (silica fume and fly ash) as dominant predictive factors. All advanced models exhibited excellent generalization (gaps < 0.02) and real-time efficiency (<0.006 s), with probabilistic uncertainty quantification enabling risk-informed infrastructure management. This research contributes to advancing machine learning applications in corrosion engineering and provides a foundation for predictive maintenance strategies in concrete infrastructure. Full article

Background: Herbal medicine represents a rich yet complex source of bioactive compounds, offering both therapeutic potential and toxicological risks. Methods: In this study, we systematically evaluated the biological effects of three traditional herbal extracts—Mentha longifolia, Scrophularia orientalis, and Echium biebersteinii—using Caenorhabditis elegans as an in vivo model. Results: All three extracts significantly reduced worm survival, induced larval arrest, and triggered a high incidence of males (HIM) phenotypes, indicative of mitotic failure and meiotic chromosome missegregation. Detailed analysis of germline architecture revealed extract-specific abnormalities, including nuclear disorganization, ectopic crescent-shaped nuclei, altered meiotic progression, and reduced bivalent formation. These defects were accompanied by activation of the DNA damage response, as evidenced by upregulation of checkpoint genes (atm-1, atl-1), increased pCHK-1 foci, and elevated germline apoptosis. LC-MS profiling identified 21 major compounds across the extracts, with four compounds—thymol, carvyl acetate, luteolin-7-O-rutinoside, and menthyl acetate—shared by all three herbs. Among them, thymol and carvyl acetate significantly upregulated DNA damage checkpoint genes and promoted apoptosis, whereas thymol and luteolin-7-O-rutinoside contributed to antioxidant activity. Notably, S. orientalis and E. biebersteinii shared 11 of 14 major constituents (79%), correlating with their similar phenotypic outcomes, while M. longifolia exhibited a more distinct chemical profile, possessing seven unique compounds. Conclusions: These findings highlight the complex biological effects of traditional herbal extracts, demonstrating that both beneficial and harmful outcomes can arise from specific phytochemicals within a mixture. By deconstructing these extracts into their active components, such as thymol, carvyl acetate, and luteolin-7-O-rutinoside, we gain critical insight into the mechanisms driving reproductive toxicity and antioxidant activity. This approach underscores the importance of component-level analysis for accurately assessing the therapeutic value and safety profile of medicinal plants, particularly those used in foods and dietary supplements. Full article

Background: Informal electronic waste (e-waste) recycling practices release a complex mixture of pollutants, particularly heavy metals, into the environment. Chronic exposure to these contaminants has been linked to a range of health risks, but the molecular underpinnings remain poorly understood. In this study, we investigated the alterations in metabolic profiles due to e-waste exposure and linked these metabolites to systemic biological effects. Methods: We applied untargeted high-resolution metabolomics using dual-column LC-MS/MS and a multi-step analysis workflow combining MS1 feature detection, MS2 annotation, and chemical ontology classification, to characterize urinary metabolic alterations in 91 e-waste workers and 51 community controls associated with the Agbogbloshie site (Accra, Ghana). The impacts of heavy metal exposure in e-waste workers were assessed by establishing linear regression and four-parameter logistic (4PL) models between heavy metal levels and metabolite concentrations. Results: Significant metal-associated metabolomic changes were identified. Both linear and nonlinear models revealed distinct sets of exposure-responsive compounds, highlighting diverse biological responses. Ontology-informed annotation revealed systemic effects on lipid metabolism, oxidative stress pathways, and xenobiotic biotransformation. This study demonstrates how integrating chemical ontology and nonlinear modeling facilitates exposome interpretation in complex environments and provides a scalable template for environmental biomarker discovery. Conclusions: Integrating dose–response modeling and chemical ontology analysis enables robust interpretation of exposomics datasets when direct compound identification is limited. Our findings indicate that e-waste exposure induces systemic metabolic alterations that can underlie health risks and diseases. Full article

Dysphagia is a common clinical condition, especially among older adults, associated with an increased risk of malnutrition, aspiration, and respiratory complications. A key therapeutic approach involves modifying liquid consistency using thickening agents to achieve safer swallowing. Although rotational rheometry offers accurate viscosity characterization, its complexity and cost limit routine application in clinical or domestic settings. This study evaluates and correlates different methods for measuring the viscosity of thickened liquids, comparing rheological data with empirical techniques such as the Ford cup, Bostwick consistometer, and Line-Spread Test (LST). Several thickeners were tested—guar gum, xanthan gum, a guar/xanthan blend, maltodextrin-based mixtures, and a commercial thickener—across a range of concentrations, temperatures, and preparation times. The results demonstrate that simple methods, particularly the Bostwick consistometer and LST, show strong correlations with rheometer measurements within the International Dysphagia Diet Standardisation Initiative (IDDSI) Level 2 (mildly thick) and Level 3 (moderately thick) ranges. However, limitations were observed at extreme viscosities, where certain methods lacked sensitivity or operational feasibility. These findings support the potential of empirical tools for practical viscosity screening in dysphagia management, especially where rheometry is unavailable. This work provides evidence-based guidance for clinicians, caregivers, and food service professionals seeking safe, reproducible, and standardized approaches to fluid consistency assessment. Full article

Information regarding the impact of polymetallic exposure on metabolic syndrome (MetS) among residents living near abandoned Pb-Zn mines is limited. Our objective was to investigate the impact of co-exposure to metal mixtures on the prevalence of MetS among residents. ICP-MS was used to measure the levels of 24 metals in the urine of 1744 participants, including 723 participants living near abandoned Pb-Zn mines, labeled as exposed area, and 1021 participants from other towns, labeled as reference area in the same city. Multivariable generalized linear regression, adaptive LASSO penalized regression, and BKMR were used to assess the associations between metals and MetS. The levels of eleven metals were higher, while those of nine metals were lower in the exposed area than those in the reference area. Mg, Cd, Ti, TI, Zn, Rb, and Pb were selected as important MetS predictors using LASSO regression. In exposed area, urinary Zn and TI were positively associated with MetS, whereas Mg was negatively associated with MetS. In the reference area, urinary Zn was positively associated with MetS, whereas Mg and Ti were negatively associated with MetS. The BKMR model indicates a statistically significant positive overall effect of the seven metal mixtures on MetS in the exposed area. Polymetallic exposure was positively associated with MetS risk in the abandoned Pb-Zn mining areas, suggesting that excessive Zn and TI may be associated with a higher MetS risk among residents living near abandoned Pb-Zn mines. Full article

Poly- and perfluoroalkyl substances (PFAS) are environmentally persistent contaminants that pose growing food safety concerns due to their potential for accumulation in edible crops. This study investigated the uptake, translocation, and tissue distribution of 11 PFAS compounds in two hydroponically grown lettuce (Lactuca sativa L.) cultivars, Agila and Bonaly. Additionally, PFAS accumulation in Agila was assessed under field conditions in a PFAS-contaminated area. Under hydroponic conditions, lettuce plants at two developmental stages (28 and 56 days after sowing) were exposed to a mixture of PFAS at concentrations of 10 and 20 µg L⁻¹ each. Under such conditions, Agila cultivar accumulated considerably higher levels of long-chain PFAS in both root and leaf tissues over time, whereas Bonaly cultivar demonstrated a more pronounced initial uptake and translocation of short-chain PFAS to leaves. Differently, Agila variety cultivated in a PFAS-polluted environment accumulated low concentrations of PFAS in leaf tissues, with only PFBA detected at minimal levels. The results emphasize the combined influence of plant variety, developmental stage, and cultivation methods on PFAS bioaccumulation, offering valuable guidance for food safety risk assessment and for developing targeted agricultural strategies in PFAS-contaminated areas. Full article

Microbiological safety and quality consistency are critical challenges in the production of traditional Indian fried snacks, particularly in small-scale food enterprises. With growing export demand, maintaining strict quality control measures is essential. This study assessed the microbiological and physicochemical quality of five traditional Indian fried snacks—Kerala Murukku, Kerala Mixture, Banana Chips, Tapioca Chips, and Achappam—produced in a Food Safety Management System (FSMS)-certified facility over a four-year period (2020–2023). Products were evaluated for moisture, pH, salt content, acid value, and Total Plate Count (TPC). The number of ingredients for each product was recorded from standardized product formulation documents. TPC levels remained within acceptable limits (below 50,000 CFU/g) across all products. Among them, Kerala Mixture consistently showed the highest microbial counts (up to 4.61 log CFU/g) and Achappam the lowest, with no detectable variance (1.00 log CFU/g). Statistically significant year-wise differences (p < 0.05) were observed in all quality parameters. Kerala Mixture showed variation in salt and microbial load; Kerala Murukku varied in moisture, pH, and salt; while Tapioca Chips varied in moisture and salt. PCA identified that TPC, salt content, number of ingredients, and pH were key contributors to product variability. Cluster analysis confirmed Kerala Mixture as the most susceptible product to contamination risk. These findings provide valuable insights into the quality trends within an FSMS-certified environment and highlight the importance of strict post-processing controls. Full article