Search Results (1,242)

Environmental pesticide exposure has been linked to adverse health effects, and residential proximity to agricultural land is commonly used as a proxy for exposure; however, the contribution of non-agricultural biomes remains insufficiently explored. This study examined whether the proximity and area of different biomes are associated with the detection of selected pesticides in human urine in Latvia. Urine samples were collected from 202 participants (101 adults and 101 children) within the Human Biomonitoring for Europe (HBM4EU) study during the winter and summer seasons of 2020. A suspect screening approach using liquid chromatography–high-resolution mass spectrometry (LC-HRMS) was applied and 23 pesticides were detected (8 insecticides, 12 fungicides, 2 herbicides and triclosan, an antimicrobial ingredient used in cleaning agents). Geospatial data were analysed in Quantum Geographic Information System (QGIS) to derive biome proximity and area within a 1000 m residential buffer; associations were assessed using generalized linear mixed-effects models. Agricultural land was present within 1000 m of 93.1% of residences, yet neither its distance nor area was consistently associated with pesticide detection. Boscalid was detected in 18.4% of samples and was positively associated with wetland area across seasons (p < 0.001), while fludioxonil (14.7%) showed weak and heterogeneous spatial associations and pirimiphos-methyl (10.2%) showed no significant patterns. Overall, pesticide exposure was substance-specific and influenced by landscape characteristics beyond agricultural proximity, highlighting the need to integrate non-agricultural biomes into human biomonitoring in low-intensity pesticide-use settings. Full article

Pesticides have been widely applied in agricultural practices over the past decades to protect crops from pests and other harmful organisms. However, their extensive use results in the contamination of soil, water, and agricultural products, posing significant risks to human and environmental health. Exposure to pesticides can lead to skin irritation, respiratory disorders, and various chronic health problems. Moreover, pesticides frequently enter surface water bodies such as rivers and lakes through agricultural runoff and leaching processes. Therefore, developing effective analytical methods for the rapid and sensitive detection of pesticides in food and water is of great importance. Electrochemical sensing techniques have shown remarkable progress in pesticide analysis due to their high sensitivity, simplicity, and potential for on-site monitoring. Two-dimensional (2D) carbon nanomaterials have emerged as efficient electrocatalysts for the precise and selective detection of pesticides, owing to their large surface area, excellent electrical conductivity, and unique structural features. In this review, we summarize recent advancements in the electrochemical detection of pesticides using 2D carbon-based materials. Comprehensive information on electrode fabrication, sensing mechanisms, analytical performance—including sensing range and limit of detection—and the versatility of 2D carbon composites for pesticide detection is provided. Challenges and future perspectives in developing highly sensitive and selective electrochemical sensing platforms are also discussed, highlighting their potential for simultaneous pesticide monitoring in food and environmental samples. Carbon-based electrochemical sensors have been the subject of many investigations, but their practical application in actual environmental and food samples is still restricted because of matrix effects, operational instability, and repeatability issues. In order to close the gap between laboratory research and real-world applications, this review critically examines sensor performance in real-sample conditions and offers innovative approaches for in situ pesticide monitoring. Full article

Exposure to plant protection products (pesticides) is common among agricultural workers and may represent an underrecognized cause of mucocutaneous disease. We conducted a descriptive cross-sectional survey in agricultural communities in southern Thailand (August–November 2025) to estimate the prevalence, clinical characteristics, and dermatology-specific quality-of-life impact of pesticide-attributed symptoms. Agricultural workers with pesticide use or exposure within the preceding 12 months were recruited via convenience sampling; participants provided consent and completed standardized interviewer-administered questionnaires assessing demographics, pesticide exposure history and application practices, personal protective equipment (PPE) use, self-reported cutaneous and mucosal symptoms (ocular and oral/nasal), and the Dermatology Life Quality Index (DLQI). Of the 354 eligible individuals, 228 participated in the study, and 226 were included in the analyses. The median age was 54 years (interquartile range [IQR], 15), and 82.7% were male. Overall, 14.6% reported pesticide-attributed cutaneous symptoms, 5.3% reported ocular mucosal symptoms, and 0.4% reported oral/nasal mucosal symptoms. Cutaneous manifestations were predominantly symptoms occurring after exposure, with pruritic, erythematous eruptions affecting the arms and hands that typically resolved within 1–7 days after cessation of exposure. Among symptomatic participants, the median DLQI was 0.5 (IQR 3.0); however, DLQI scores were significantly higher among participants who reported pesticide-attributed cutaneous symptoms (p < 0.001) and ocular symptoms (p < 0.001). These findings suggest that pesticide-associated mucocutaneous effects are generally mild yet clinically meaningful, underscoring the need to strengthen PPE training, risk communication, and occupational health surveillance in agricultural settings. Full article

Drought stress and insecticide exposure are two significant environmental factors that can impact the physiology and behaviour of aphids, a major agricultural pest. An understanding of the mechanisms of green peach aphids’ response to insecticides under drought stress is a critical area of research that needs urgent attention. In view of this, we conducted this study to determine the impact of drought and insecticides on the activity of detoxification enzymes in green peach aphid. A 2 × 2 × 3 factorial experiment involving two levels of water treatments (drought and no drought), two levels of aphids infestation (aphids and no aphids), and three levels of pesticides applications (thiacloprid, flonicamid and no pesticide) was conducted. The treatments were arranged in a randomized complete block design with three replications. The results showed that there was a significant (p < 0.01) interaction effect of drought × insecticides on the green peach aphid performance under drought or no drought conditions. Generally, the highest aphids host acceptance, survival rate, colonization success, and average daily reproduction under drought and well-watered conditions occurred on flonicamid-treated plants, whereas thiacloprid-treated plants had the least. However, the thiacloprid-treated plants had higher photosynthetic rate, water use efficiency, lower stomatal conductance, and decreased transpiration rate. Moreover, flonicamid treatment increased the accumulation of glutathione–S-transferase, acetylcholinesterase, butyrylcholinesterase, 1-napthyle acetate, and 1-napthyle butyrate activities in aphids, compared to the thiacloprid treatments. The thiacloprid pesticide, which demonstrated higher efficacy against green peach aphid, can be used in areas where green peach aphids and drought stress are major concerns. Full article

Over the last 15 years, mixture risk assessment for food xenobiotics has evolved from conceptual discussions and simple screening tools, such as the Hazard Index (HI), towards operational, component-based and probabilistic frameworks embedded in major food-safety institutions. This review synthesizes methodological and regulatory advances in cumulative risk assessment for dietary “cocktails” of pesticides, contaminants and other xenobiotics, with a specific focus on food-relevant exposure scenarios. At the toxicological level, the field is now anchored in concentration/dose addition as the default model for similarly acting chemicals, supported by extensive experimental evidence that most environmental mixtures behave approximately dose-additively at low effect levels. Building on this paradigm, a portfolio of quantitative metrics has been developed to operationalize component-based mixture assessment: HI as a conservative screening anchor; Relative Potency Factors (RPF) and Toxic Equivalents (TEQ) to express doses within cumulative assessment groups; the Maximum Cumulative Ratio (MCR) to diagnose whether risk is dominated by one or several components; and the combined Margin of Exposure (MOET) as a point-of-departure-based integrator that avoids compounding uncertainty factors. Regulatory frameworks developed by EFSA, the U.S. EPA and FAO/WHO converge on tiered assessment schemes, biologically informed grouping of chemicals and dose addition as the default model for similarly acting substances, while differing in scope, data infrastructure and legal embedding. Implementation in food safety critically depends on robust exposure data streams. Total Diet Studies provide population-level, “as eaten” exposure estimates through harmonized food-list construction, home-style preparation and composite sampling, and are increasingly combined with conventional monitoring. In parallel, human biomonitoring quantifies internal exposure to diet-related xenobiotics such as PFAS, phthalates, bisphenols and mycotoxins, embedding mixture assessment within a dietary-exposome perspective. Across these developments, structured uncertainty analysis and decision-oriented communication have become indispensable. By integrating advances in toxicology, exposure science and regulatory practice, this review outlines a coherent, tiered and uncertainty-aware framework for assessing real-world dietary mixtures of xenobiotics, and identifies priorities for future work, including mechanistically and data-driven grouping strategies, expanded use of physiologically based pharmacokinetic modelling and refined mixture-sensitive indicators to support public-health decision-making. Full article

The fall armyworm, Spodoptera frugiperda, has become one of the most damaging agricultural pests worldwide, yet the genetic basis of its extraordinary adaptability remains elusive. Recent studies have highlighted the pivotal role of newly evolved genes in adaptive evolution, and phylostratigraphy has emerged as a powerful conceptual framework to trace their origins. Here, we adopt this framework to investigate how new genes have contributed to the rapid adaptive evolution of S. frugiperda. Using high-quality genomic data, we inferred gene ages across evolutionary phylostrata and identified 277 newly evolved genes that originated after the divergence of Spodoptera. These new genes exhibit hallmark genomic signatures of recent origin, including shorter coding regions, simplified structures, and relaxed evolutionary constraints. Interestingly, transcriptomic analyses revealed strong tissue specificity, with pronounced enrichment in the antenna and brain, indicating possible involvement in chemosensory and neural functions essential for environmental and behavioral adaptation. Under diverse environmental challenges such as pesticide and parasitoid wasp exposure, and virus infection, we found many of the new genes acted as hubs in the regulatory networks associated with pesticide response. Together, our findings suggest that the emergence of new genes has played a critical role in shaping the rapid adaptive evolution of S. frugiperda and provide broader insights into how newly evolved genes contribute to species adaptation. Full article

Background: Gestational diabetes mellitus (GDM) is a frequent pregnancy pathology with poor maternal and fetal outcomes and risk of type 2 diabetes in later life. Despite known risk factors, such as obesity, age, and familial history, new data suggest that environmental exposure to agents, such as pesticides, can play a role in the etiogenesis of GDM. Objective: The epidemiologic, experimental, and mechanistic evidence between pesticide exposure and GDM risk is summarized here, and we concentrate on recent research (2000–2025). Methods: We conducted a literature search in PubMed, Embase, and the Cochrane Library for studies published from January 2000 to December 2025 using combinations of the terms “fertilizers”, “herbicides”, and “pesticides” with “diabetes mellitus” and “gestational diabetes”. After deduplication, 12 unique studies met inclusion criteria for qualitative synthesis (GDM endpoint or pregnancy glycemia with pesticide exposure). Results: Occupational and agricultural exposure to pesticides during first pregnancy was determined to be associated with a significantly increased risk of GDM through various epidemiologic studies. New studies have implicated new classes of pesticides, including pyrethroids and neonicotinoids, with higher GDM risk with first-trimester exposure. Experimental studies suggest that pesticides provide potential endocrine-disrupting chemicals that can induce insulin resistance through disruption of hormonal signaling, oxidative stress, inflammation, β-cell toxicity, and epigenetic modifications. However, significant limitations exist. Most of the evidence is observational, measurement of exposure is often indirect, and confounding factors are difficult to exclude. Notably, low dietary and residential exposure is not well studied, and dose–response relationships are undefined. Conclusions: New data indicate that pesticide exposure during early pregnancy and occupational exposure may increase the risk of GDM. Prospective cohort studies using biomonitoring, chemical mixture exposure, and geographic variation in pesticide exposure should be the focus of future research. Due to potential public health implications, preventive strategies to ensure the quality of nutrition and to reduce maternal exposure to pesticides during pregnancy are rational. Full article

The widespread use of antibiotics, combined with pervasive exposure to diverse environmental media, has intensified the global challenge of antibiotic resistance. Accumulating evidence reveals that beyond direct antibiotic pressure, residual non-antibiotic chemicals—despite lacking intrinsic antibacterial activity—can significantly promote the enrichment and spread of antibiotic resistance genes (ARGs) in farmland soils through indirect mechanisms such as inducing oxidative stress, altering microbial community structure, and enhancing both vertical and horizontal gene transfer. To address this issue, the present study investigates the influence of representative non-antibiotic contaminants commonly detected in agricultural environments—including pesticides (e.g., Omethoate, imidacloprid, and atrazine), industrial pollutants (e.g., PCB138, BDE47, benzo [a] pyrene, 2,3,7,8-tetrachlorodibenzo-p-dioxin [TCDD], and benzene), plastic-associated compounds (e.g., Polyethylene trimer, phthalates, and tributyl acetylcitrate), and ingredients from personal care products (e.g., triclosan and bisphenol A)—on ARG transmission dynamics. Leveraging bioinformatics resources such as the CARD database, PDB, AlphaFold, and molecular sequence analysis tools, we identified relevant small-molecule ligands and macromolecular receptors to construct a simulation system modeling ARG transfer pathways. Molecular docking and molecular dynamics (MD) simulations were then implemented, guided by a Plackett–Burman experimental design, to systematically evaluate the impact of individual and co-occurring pollutants. The resulting data were processed using advanced analytical tools, and MD trajectories were interpreted at the molecular level across three scenarios: an unperturbed (blank) system, single-pollutant exposures, and dual-pollutant combinations. By integrating computational simulations with machine learning approaches, this work uncovers the “co-selection” effect exerted by non-antibiotic chemical residues in shaping the environmental resistome, thereby providing a mechanistic and scientific basis for comprehensive risk assessment of agricultural non-point source pollution and the development of effective soil health management and antimicrobial resistance containment strategies. Full article

The widespread presence of polystyrene microplastics (PS-MPs) and agricultural pollutants such as avermectin (AVM) in aquatic environments poses a significant threat to aquatic organisms. However, the combined toxic effect of PS-MPs and AVM on cardiac development remains poorly understood. This study aimed to investigate the cardiac toxicity of AVM co-exposed with two sizes of MPs (large MPs, LMPs, 20 µm; small MPs, SMPs, 80 nm) in both larval and adult zebrafish. Firstly, under the co-exposure conditions of MPs and AVM, we observed significant cardiac developmental toxicity, including decreased survival rate, body length, and hatching rate, as well as a significant reduction in the number of myocardial cells. Secondly, the number of neutrophils and antioxidant enzyme activities such as CAT and SOD were greatly decreased, while inflammatory cytokines such as TNF-α and IL8 were significantly increased after co-exposure in larval zebrafish. Thirdly, there was severe disorganization of cardiomyocytes and interstitial edema in adult zebrafish hearts under the co-exposure by histopathological examination. Our results suggest that cardiomyocyte proliferation was suppressed, but heart apoptosis level and anti-apoptotic genes were significantly increased in the AVM+MPs co-exposure. Additionally, transcriptome sequencing and bioinformatics analysis revealed that significant changes in differentially expressed genes in the AVM+SMPs co-exposure group, particularly in the processes related to oxidation–reduction, inflammatory response, and the MAPK signaling pathway in the adult zebrafish heart. Furthermore, our pharmacological experiments demonstrated that inhibiting ROS and blocking the MAPK signaling pathway could partially rescue the heart injury induced by AVM and MPs co-exposure in both larval and adult zebrafish. In summary, this study suggested that co-exposure to AVM and MPs could induce heart toxicity mainly via the ROS-mediated MAPK signaling pathway in zebrafish. The information provided important insights into the potential environmental risk of microplastic and pesticide co-exposure on aquatic ecosystems. Full article

Background: Viticulture in Southern Brazil heavily relies on fungicides, such as Mancozeb, to manage fungal diseases. Increasing concern has emerged regarding the chronic health effects of Mancozeb exposure among vineyard workers, particularly its potential to induce oxidative stress and genotoxicity. Methods: A cross-sectional study was conducted between July and November 2023 involving 94 participants: 50 vineyard workers occupationally exposed to Mancozeb and 44 organic farmers with no history of pesticide exposure, who served as the control group. Eligible participants were aged 18 years or older, and exposed individuals had at least 5 years of documented Mancozeb use. Data on demographics, health status, occupational history, and use of personal protective equipment (PPE) were collected through structured interviews. Blood and urine samples were analyzed to determine hematological and biochemical parameters, oxidative stress biomarkers, genotoxicity (via comet assay and micronucleus test), and urinary ethylene thiourea (ETU), the primary metabolite of Mancozeb. Results: Workers exposed to Mancozeb exhibited significantly elevated levels of oxidative stress markers (p < 0.001) and DNA damage in both genotoxicity assays (p < 0.001). Urinary ETU concentrations were also markedly elevated, and a threshold of 69.3 ng/mL was identified as a discriminative marker of exposure. Conclusions: This study offers a novel contribution by proposing a specific biological exposure limit for ETU concentrations, derived from ROC curve analysis, representing a significant advancement in occupational health. The findings underscore the urgent need for regulatory biological exposure limits and the implementation of effective preventive strategies. Full article

Neonicotinoid insecticides were initially hailed as safer alternatives to organochlorine and organophosphate pesticides due to their perceived lower toxicity to non-target organisms. However, it has been recently discovered that sublethal exposure to neonicotinoids negatively affects beneficial arthropods that are essential for a functional ecosystem. These beneficial arthropods include pollinators, biological control agents, and decomposers. This review synthesizes current research on the physiological, behavioral, and reproductive consequences of neonicotinoids on non-target arthropods and their broader ecological impact. The chemical and physical properties of neonicotinoids raise concerns about long-term ecological consequences of neonicotinoid use because these chemicals are persistent in plants and soil, which contributes to prolonged exposure risks for organisms. Sublethal doses of neonicotinoids can disrupt the ecological services provided by these organisms by impairing essential biological processes including motor function, odor detection, development, and reproduction in insects, while also altering behavior such as foraging, mating, and nesting. Furthermore, neonicotinoid exposure can alter community structure, disrupting trophic interactions and food web stability. Recognizing the sublethal impacts of neonicotinoids is critical for the development of more sustainable pest management strategies. It is imperative that future research investigates the underlying mechanisms of sublethal toxicity and identifies safer, more effective approaches to neonicotinoid-based pest control to mitigate adverse ecological effects. Incorporating this knowledge into future environmental risk assessments will be essential for protecting biodiversity and maintaining ecosystem functionality. Full article

This review provides a comprehensive overview of strategies to mitigate pesticide residues in food, examining both household and industrial processing techniques alongside the emerging role of Artificial Intelligence (AI). Simple household methods, such as washing, peeling, and thermal processing (e.g., boiling, frying), are effective. For instance, washing with running water achieves a reduction of up to 77% in residue for some vegetables. Additionally, processes like jam-making or frying can significantly reduce specific residues. Industrially, advanced methods such as ozonated water washing, ultrasonification, and cold plasma are employed for high efficiency while preserving food quality. Critically, AI is emerging as a powerful, indirect tool through predictive modelling, AI-assisted sorting/screening, and consumer guidance, enhancing precision agriculture and regulatory analytics. The review paper concludes that a combination of these diverse methods is essential for minimizing pesticide exposure and ensuring a safer food supply. Full article

A wide range of non-microbial contaminants—such as heavy metals, pesticide residues, antibiotics, as well emerging foodborne contaminants like micro- and nanoplastics and persistent organic pollutants—can enter the human body through daily diet and exert subtle yet chronic effects that are increasingly recognized to be gut microbiota-dependent. However, the relationships among multi-contaminant exposure profiles, dynamic microbial community structures, microbial metabolites, and diverse clinical or subclinical phenotypes are highly non-linear and multidimensional, posing major challenges to traditional analytical approaches. Artificial intelligence (AI) is emerging as a powerful tool to untangle the complex interactions between foodborne non-microbial contaminants, the gut microbiota, and host health. This review synthesizes current knowledge on how key classes of non-microbial food contaminants modulate gut microbial composition and function, and how these alterations, in turn, influence intestinal barrier integrity, immune homeostasis, metabolic regulation, and systemic disease risk. We then highlight recent advances in the application of AI techniques, including machine learning (ML), deep learning (DL), and network-based methods, to integrate multi-omics and exposure data, identify microbiota and metabolite signatures of specific contaminants, and infer potential causal pathways within “contaminant–microbiota–host” axes. Finally, we discuss current limitations, such as data heterogeneity, small-sample bias, and interpretability gaps, and propose future directions for building standardized datasets, explainable AI frameworks, and human-relevant experimental validation pipelines. Overall, AI-enabled analysis offers a promising avenue to refine food safety risk assessment, support precision nutrition strategies, and develop microbiota-targeted interventions against non-microbial food contaminants. Full article

Carbofuran, a widely used carbamate pesticide, is an endocrine disruptor with documented reproductive toxicity, yet the mechanisms underlying its ovarian toxicity remain incompletely understood. This study employed integrated network toxicology and untargeted metabolomics to investigate these mechanisms in female C57BL/6J mice that had been chronically exposed to carbofuran (0.5 or 2.0 mg/kg for 45 days, once daily). Methods included histopathological evaluation, serum hormone ELISA, network prediction of toxicity targets, molecular docking, and metabolomics profiling. Results demonstrated that carbofuran exposure induced dose-dependent ovarian damage, including reduced follicular reserve, increased atresia, abnormal corpus luteum, and disrupted hormone levels. Network toxicology identified 38 common targets, with EGFR, GSK3B, APP, and JAK2 as core proteins, indicating potential high affinity. Metabolomics suggests significant alterations in pathways such as phenylalanine, tyrosine, tryptophan biosynthesis and arginine/proline metabolism. Our collective evidence indicates that carbofuran may induce ovarian toxicity through multifaceted mechanisms involving endocrine disruption, oxidative stress, inflammatory activation, and metabolic disturbance. This study provides novel experimental insights into the reproductive toxicity mechanisms of carbofuran, offering a theoretical basis for health risk assessment and intervention strategies. Full article

Chlorpyrifos (CPF), a widely used organophosphate pesticide, induces hepatotoxicity primarily through oxidative stress, acetylcholinesterase (AChE) inhibition, and inflammatory responses. This study evaluated the hepatoprotective potential of detoxifying formulations prepared from four medicinal plants, Thunbergia laurifolia, Embelia sessiliflora, Morinda angustifolia, and Thunbergia coccinea, in various ratios. Among these, a formulation composed of T. laurifolia and E. sessiliflora (1:1; Formula 04) showed the highest activity, with rosmarinic acid identified by compact mass spectrometry (CMS). Formula 04 demonstrated the greatest antioxidant and pro-apoptotic potential among the seven tested formulations, as confirmed by in vitro DPPH and superoxide radical assays and apoptosis assays in hepatic stellate LX-2 cells. In vivo, Sprague–Dawley rats exposed to CPF (16 mg/kg/day, oral gavage) received Formula 04 orally 30 min prior to CPF exposure in 6 cyclic dosing regimen for 18 days. The treatment restored AChE activity, increased superoxide dismutase levels, reduced glutathione levels, and decreased malondialdehyde, indicating attenuation of oxidative stress. Serum AST levels were significantly reduced compared with the CPF group, and histopathology revealed that the hepatic architecture was preserved. These findings demonstrate that Formula 04 exerts hepatoprotective effects against CPF-induced toxicity via redox regulation and cellular protection mechanisms, demonstrating its potential as a natural detoxifying agent. Full article