Science of The Total Environment

Mercury biomagnification in Amazonian rivers is usually assessed through fishes, yet contaminants can also move across riparian food webs through multiple energy pathways. We evaluated how total mercury (THg) is structured across the upper Caqueta River basin, a mining-impacted river floodplain system in the Colombian Amazon. Using stable carbon and nitrogen isotopes, trophic guild classification, biomagnification models, and Bayesian mixing models, we integrated basal resources, macroinvertebrates, fishes, and birds to link mercury exposure with food-web architecture. THg increased with trophic enrichment in fishes, birds, and the combined food web, indicating biomagnification across aquatic and aquatic-associated consumers. Reconstructed pathways showed that phytoplankton and detritus support intermediate fish consumers, which in turn connect basal production to carnivore piscivorous fishes and aquatic predatory birds. Avian results suggest that mercury exposure is not restricted to aquatic predators, as hummingbirds showed unexpectedly elevated THg values that may reflect additional riparian or arthropod-mediated pathways. Overall, mercury transfer in the upper Caqueta emerges from the interaction between trophic position and energy-flow structure, highlighting the need to evaluate contamination magnification through integrated aquatic riparian food webs rather than single consumer groups.

Food security is one of the major ongoing global anthropic challenges, driving the intensification of agricultural systems notably through the widespread use of phyto-pharmaceutical products (PPPs). Although effective for maximizing production yields through pest control, PPP contamination is pervasive across the entire agroecosystem, raising concerns about human and non-target species exposure and health effects. Organic farming has therefore been promoted as a sustainable alternative to ensure human food security and mitigate these impacts. Yet, the pathways of PPP non-target organisms contamination are insufficiently understood. While most research has focused on ingestion as the primary route of exposure, increasing evidence suggests more complex contamination dynamics. In this study, we investigated the role of food intake in shaping PPP contamination profiles in semi-captive grey partridges (Perdix perdix). To do so, 80 birds were housed in open aviaries within an agricultural landscape and fed either conventional or organic grains over a five-month period. After drawing their PPP blood profiles at the end of the exposure period, we assessed their loads and compared the pesticide prevalence and abundance between food treatments. We found similar quantity and diversity of PPP residues in blood from conventionally- and organically-fed partridges, with few differences in specific PPP compounds. Overall, these findings suggest that food intake is not necessarily the only source of contamination for non-target organisms, with alternative pathways (e.g., inhalation, dermal contact, soil and water exposure) likely playing a substantial role. Integrating multi-pathway contamination monitoring across trophic levels within a One Health framework would now be essential to better understand and mitigate PPP contamination risks. Submitted to PCI: Ecotoxicology and Environmental Chemistry

Heavy metal contamination in soil systems is an escalating global crisis, yet over 55% of urban agriculture literature focuses on high-tech indoor vertical farming, leaving vulnerable open-field tropical urban agriculture (UPA) severely under-researched. This study addresses this knowledge gap by evaluating the chemical mechanics of heavy metal translocation within highly acidic Xanthic Ferralsols in Fendall, Liberia, serving as a global proxy for tropical agro-ecosystem risks. Using a randomized complete block design, topsoil (0-20 cm) from five cultivated and five uncultivated sites (n = 10) and corresponding tissues of cabbage (Brassica oleracea), lettuce (Lactuca sativa), and sweet potato greens (Ipomoea batatas) were screened via handheld X-ray fluorescence spectrometry. Results revealed a compelling geochemical paradox: uncultivated soils demonstrated significantly higher geogenic background metal concentrations across all elements (p < 0.05). Systemic Nickel (Ni) above the World Health Organization (WHO) thresholds was recorded on both land-use histories. While plant tissues accumulation of Copper (Cu) and Zinc (Zn) remained within safe parameters, Lead (Pb) concentrations across all crops profoundly exceeded food safety standards, averaging 1.53 mg/kg, which is over 5 times above the WHO limit (0.30 mg/kg). Risk screening highlighted high soil-to-plant transfer factors (TF =>1) for Ni and Zn in plant tissue, in the order of cabbage > sweet potato greens > lettuce. These findings provide transferable insights into how high soil acidity accelerates toxic metal mobilization, offering a scalable framework for crop-specific exclusion policies and real-time field screening in tropical municipalities. AbstractRapid urban agricultural expansion in Montserrado County, Liberia, relies heavily on highly weathered acidic Xanthic Ferralsols. While these soils support crop growth, they present a hidden geogenic risk of heavy metal translocation to the human food chain. This study evaluated the concentrations of Copper (Cu), Nickel (Ni), Lead (Pb), and Zinc (Zn) in the soils and edible tissues of cabbage (Brassica oleracea), lettuce (Lactuca sativa), and sweet potato greens (Ipomoea batatas) in Fendall. The uncultivated soils exhibited a geochemical paradox, showing significantly higher total metal concentrations than cultivated plots. However, low soil pH (4.0-6.0) highly mobilized these geogenic metals, driving rapid plant uptake. While tissue concentrations of Cu, Ni, and Zn remained within safe physiological ranges, Lead (Pb) concentrations in all three crops reached an alarming mean of 1.53 mg/kg, exceeding the World Health Organization (WHO) permissible safety limit of 0.30 mg/kg by more than 5-fold. The soil-to-plant Transfer Factors (TF) for Lead ranged from 0.51 to 0.81, highlighting significant bioavailable translocation despite the lack of visible crop phytotoxicity. These results demonstrate that passive geogenic metal uptake poses a silent public health threat. Immediate agronomic interventions, including systematic liming and crop-exclusion frameworks, are urgently required to safeguard urban food security in Monrovia. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/740606v1_ufig1.gif" ALT="Figure 1"> View larger version (111K): org.highwire.dtl.DTLVardef@1171648org.highwire.dtl.DTLVardef@b7f56eorg.highwire.dtl.DTLVardef@15227e6org.highwire.dtl.DTLVardef@b996bf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Ecological forecasts often rely on established relationships between the ecological process of interest and predictor variables that are more easily measured. Proliferations of benthic (i.e., bottom-dwelling) cyanobacteria have been increasingly observed in rivers globally and are an emerging ecological forecasting issue as they pose a public health threat due to the production of potent neurotoxins known as anatoxins. Controls on these benthic cyanobacteria are poorly understood, thus predicting or forecasting their extent and anatoxin production is a significant challenge. Here, we measured benthic cyanobacterial cover and anatoxin concentrations for two common taxa associated with anatoxins (Microcoleus and Anabaena) at biweekly to weekly intervals during June to September in 2022 and 2023 in three northern Californian rivers. We then built predictive models to test how incorporation of a biotic predictor (river reach-scale gross primary productivity [GPP]) affected predictive accuracy in addition to widely measured abiotic predictors (i.e., nutrients, discharge, and temperature). Temporal patterns in taxon-specific benthic cyanobacterial cover and anatoxin concentrations were highly variable among rivers and between taxa. While Microcoleus cover peaked in rivers during periods of relatively low GPP, there were no clear relationships between GPP and Anabaena cover nor anatoxin concentrations of either taxon among rivers. Among multiple reaches sampled weekly in the South Fork Eel River, magnitudes of taxon-specific benthic cyanobacterial cover and anatoxin concentrations differed, but the timing of peak taxon-specific cover and anatoxin concentrations were generally consistent. Furthermore, Anabaena displayed a hysteresis relationship where increases in cover were followed by increases in anatoxin concentrations while Microcoleus lacked such relationship. While incorporating GPP as a covariate improved our predictions of Anabaena cover, we had more success predicting Microcoleus cover than Anabaena cover due to its strong negative relationship with discharge. In contrast, our models predicting Anabaena anatoxin concentrations outperformed those predicting Microcoleus anatoxin concentrations due to the hysteresis relationship between Anabaena cover and anatoxins. Overall, our predictive modeling results highlight the application of ecological forecasting for benthic cyanobacterial cover and anatoxin concentrations in rivers and demonstrate the importance of incorporating taxon-specific predictors into future forecasts of benthic cyanobacteria.

Background: Guanica, Puerto Rico, has one of the highest concentrations of environmental polychlorinated biphenyls (PCBs). This PCB contamination coupled with persistent poverty, population loss, and repeated environmental disasters has taken a heavier toll on Guanica community. Our environmental sampling has documented high levels of PCBs in sediment, air and fish, but far less is known about how residents themselves understand exposure, interpret health risk, and weigh contamination against the other pressures of daily life. Methods: We used a qualitative descriptive design nested within the larger HELP Study. This paper presents the final analysis of all qualitative data collected in Guanica: ten sessions comprising five focus groups and five interviews with fishermen (N = 31), conducted between November 2024 and October 2025 in familiar community settings. Sessions followed a semi-structured guide translated from English to Spanish and back-translated for accuracy. Recordings were transcribed in Spanish, verified against the audio, and analyzed in NVivo using codebook-style thematic analysis; three bilingual researchers coded collaboratively and resolved disagreements by consensus. Results: Five themes emerged from our analysis concerning how residents and fishermen understand and navigate PCB contamination: (1) perceived community decline shapes how residents prioritize environmental risks; (2) limited knowledge, misinformation, and communication gaps affect understanding of PCB contamination; (3) cancer concerns are high, but links to PCB exposure remain unclear; (4) PCB contamination is seen as a threat to livelihoods, especially fishing and tourism; and (5) deep mistrust and a desire for accountability influence perceptions of environmental interventions. Participants described contamination not as an isolated hazard but as one strand of a longer history of economic decline, disaster, and institutional neglect. Conclusions: Social, economic, and environmental conditions together shape how Guanica residents perceive contamination of their environment. Meaningful progress requires sustained community involvement, support for local initiatives, development of a Community Health Worker program, and expanded partnerships with local institutions and schools to close communication gaps and promote long-term resilience to address the health effects of PCB contamination in Guanica.

This study assesses the spatial dynamics of heavy metals and associated trace elements in the water and sediment of the Slana River approximately one and half year after an environmental accident and river contamination caused by mining effluent. Using PCA and standardized environmental indices (CF, PLI), we modelled the distribution of contaminants across the macro-gradient of the river and within the micro-gradient surrounding the source of pollution. We found that although the situation in the water column has improved and stabilized, the sediment remains the primary reservoir of trace elements, including toxic arsenic, with the highest concentrations recorded near the source and in its immediate vicinity. Although the concentration of primary mining indicators decreases relatively rapidly along the stream, this is systematically offset by the accumulation of other elements, including sulphur and aluminium. As a result of these geochemical processes, the total pollution load index (PLI) remains statistically unchanged along the entire stream, but indicates a chronic, spatially uniform (PLI = 1.06-1.16) toxicological burden on the ecosystem.

Long-term PM2.5 exposure is associated with increased mortality and is usually represented by annual mean concentration, which does not capture how concentrations are distributed across days. We tested whether the prespecified PM2.5 magnitude-rank index (PMRI), a summary of within-year daily concentration structure, improves mortality prediction beyond the annual mean. Daily modeled PM2.5 estimates were linked to age-adjusted mortality rates for 27,289 county-years from 3,064 U.S. counties during 2003-2011. PMRI is the largest k for which at least k days reached k micrograms per cubic meter. County-grouped 10-fold cross-validation compared models with annual mean alone versus annual mean plus PMRI, with additional geographic, temporal, cause-specific, and specification analyses. Annual mean PM2.5 had the highest standalone predictive performance. Adding PMRI increased county-held-out R-squared from 0.0802 to 0.1391 (increase in R-squared = 0.0589; 95% CI, 0.0499-0.0677) and reduced RMSE and MAE. Improvement persisted across geographic and temporal validations and all six cause-specific mortality outcomes. Within-year PM2.5 exposure structure therefore contains reproducible mortality-predictive information not captured by annual mean concentration.

Surface water quality is a significant public health concern because contaminated rivers and lakes can spread waterborne diseases and expose communities to harmful pollutants, particularly in areas where water treatment and regulation are limited. This study assesses the anthropogenic impact on surface water quality in the Ahafo Ano Southwest District, Ghana. Water samples were collected from three locations within the Mankran watershed during both wet and dry seasons and analyzed for key parameters. Pollutant concentrations exhibited marked spatial and seasonal variability, with nitrate ranging from 1.09 to 13.77 mg/L, phosphate from 1.58 to 10.55 mg/L, and total suspended solids from 140.0 to 1680.0 mg/L. Heavy metals frequently exceeded acceptable limits, with zinc ranging from below detection to 0.11 mg/L, copper from below detection to 0.84 mg/L, and lead from below detection to 0.46 mg/L. Seasonal Water Quality Index (WQI) analysis indicated degraded water quality during the wet season in Baniekrom and Kunsu, due to increased runoff carrying agricultural residues, sediments, and mining contaminants. In contrast, Mmobrem showed improved wet-season quality, attributed to rainfall dilution. The Piper diagram further revealed that the water samples predominantly fall within the Ca-Cl hydrochemical facies, reflecting strong geogenic control through basaltic rock weathering, coupled with chloride enrichment likely intensified by agricultural and domestic inputs. Principal component analysis indicated that multiple anthropogenic and natural factors drive water quality variations across the catchment. Ecological risk assessment identified potential risks to algae, resulting from elevated levels of nutrients and metals. Overall, the combined WQI and hydrochemical evidence indicate an intensified nutrient influx during the wet season and increased suspended particulate matter during the dry season, primarily driven by agriculture, deforestation, and mining. The findings underscore the urgent need for sustainable water management strategies to mitigate the impacts of human activities on surface water quality in the region.

Despite their fundamental role in sustaining terrestrial biodiversity and ecosystem functioning, soils are increasingly contaminated by pesticides, often occurring as complex mixtures. Understanding chemical uptake, distribution, and elimination in soil organisms is essential for reliable risk assessment. We investigated the toxicokinetics of a binary mixture of imidacloprid and epoxiconazole in the earthworm Aporrectodea caliginosa. Single-substance experiments were conducted to estimate uptake and elimination rates, and allowed the implementation of single substance toxicokinetic models. A mixture experiment tested five concentration ratios to assess potential interactions. Epoxiconazole, an azole fungicide, exhibited rapid uptake and elimination (k_u = 1.9 gsoil*gworm-1*d-1; k_e = 1.7 d-1), resulting in low bioaccumulation (BAF = 0.9), whereas imidacloprid, a neonicotinoid insecticide, accumulated slowly with low elimination (k_u = 1.6 gsoil*gworm-1* d-1; k_e = 0.12 d-1), producing high bioaccumulation (BAF = 20). The explicit inclusion of the 24-hour Petri dish depuration phase proved to be critical, especially for epoxiconazole, highlighting the influence of gut-clearance procedures on apparent kinetics. In accordance with only a small synergistic effect in the mixture, no toxicokinetic interactions were detected in the mixture; internal concentrations of each compound were consistent across ratios. Concentration-dependent patterns were observed, with indications of a saturation process at high exposure levels for imidacloprid, and an increased BAF at high concentrations for epoxiconazole. This finding questions the use of single, concentration-independent bioaccumulation factors for hazard assessment and highlights the value of integrated TKTD approaches.

Plants emit substantial amounts of biogenic volatile organic compounds (VOCs) that link plant physiological activity to ecological interactions and atmospheric chemistry. However, the processes regulating VOC emissions within the forest air and at the interface directly above the canopy remain poorly characterized. In this study, we investigated forest-scale VOC dynamics in a cool-temperate deciduous forest dominated by Quercus crispula using high-time- and high-mass-resolution proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) integrated with positive matrix factorization (PMF). This non-targeted, process-oriented framework was applied to forest-interior and canopy-top atmospheres during rain-free summer days in 2024 and 2025 to extract dominant modes of VOC emissions. The PMF consistently resolved two recurring modes characterized by the daytime and nighttime enhancement patterns. The daytime mode was dominated by isoprene and its oxidation products and demonstrated strong light- and temperature-dependence, whereas the nighttime mode was enriched in mono- and sesquiterpenes. The daytime contribution exhibited a pronounced morning-afternoon asymmetry, indicating non-linear physiological and canopy-scale controls. These patterns were reproducible across the years. This study demonstrates that combining PTR-ToF-MS with PMF enables robust, top-down identification of recurring modes of forest VOC variability within and above forest canopies, linking leaf-level physiology and ecosystem-scale atmospheric exchange. HighlightForest-scale VOC emissions were resolved into recurring daytime and nighttime modes using a non-targeted PTR-ToF-MS and PMF framework.

Hormesis is an important consideration in chemical risk assessment across most aquatic environments. Evidence suggests that hormetic responses are shaped by organismal physiological processes. Accordingly, predictions of hormesis under environmentally realistic conditions should account for physiological traits. Yet the role of these traits remains largely unexplored. This study investigated how baseline growth rate modulates antibiotic responses in the harmful cyanobacterium Microcystis and the underlying mechanisms. Results showed that at an antibiotic concentration of 200 ng L-1 (representing environmental concentration levels), slow-growing Microcystis populations exhibited an obvious growth enhancement more than 4-fold greater than that of fast-growing populations, and this enhancement was positively correlated with cellular reserves. A baseline growth rate below 0.19 day-1 emerged as the threshold below which hormetic responses were consistently observed. This study provides pioneering insights into how organisms' physiological states influence pollutant-induced hormetic responses in aquatic environments. Our findings point to a central principle for extrapolation that laboratory-derived toxicological responses may not translate directly to the field unless key physiological traits of the organisms are explicitly considered. In this regard, baseline growth rate and energy reserves may be key physiological traits for reliably predicting toxic effects at the population level. This study also makes an initial attempt to conceptualize a physiology-anchored framework for strengthening risk assessment of low-level emerging contaminants.

Subsurface tile drainage rapidly transports nutrients and biological contaminants to surface waters, yet multi-year evaluations of drainage water management (DWM) effects on nutrients, Escherichia coli, and antibiotic resistance genes (ARGs) remain limited. A paired-field design with high-frequency soil moisture monitoring was used to quantify water yield, dissolved nitrogen, phosphorus, and Escherichia coli (E. coli) over seven and eight water years, and ARGs (tetM, tetW, ermB, sul1) over two years in southern Michigan. Soil moisture at tile depth (~75 cm) was higher under controlled drainage, confirming that DWM increases field water-holding capacity. Compared to the free drainage field, DWM reduced cumulative tile discharge by 43% and annual nutrient yields by 46-83% for nitrate and 12-82% for soluble reactive phosphorus, but effects on ammonium were variable. Average daily nutrient yields declined by ~50% over the study period, driven primarily by managed periods. Nutrient concentrations did not differ between treatments, indicating that yield reductions resulted from decreased water loss. Mean daily E. coli yields declined by 71% over the study period, and concentrations were 46% lower under controlled drainage. Controlled drainage reduced tetM and sul1 ARG concentrations and yields during managed periods and throughout the study; however, sensitivity analyses showed that these effects were strongly influenced by a high-precipitation event. After excluding the event, differences in ARG concentrations were no longer detected, although ARG yields remained 43% lower during managed periods. These findings highlight the potential for DWM to mitigate nutrient, microbial, and antibiotic resistance transport from agricultural drainage systems.

Hexafluoropropylene oxide dimer acid (GenX), a replacement for legacy per- and polyfluoroalkyl substances (PFAS), is increasingly detected in the environment, yet its chronic toxicity remains poorly characterized. Current safety assessments rely largely on short-term, high-dose studies that may not capture the biological consequences of long-term, low-dose exposure. To address this gap, we employed 3D human liver (HepG2/C3A) spheroids cultured in a continuously rotating bioreactor system (ClinoStar) to systematically evaluate dose- and time-dependent mRNA changes in response to GenX under environmentally relevant conditions. Spheroids were exposed to GenX (0.08-50 M, spanning environmentally relevant to mechanistically informative concentrations) for acute (4 days) and chronic (4 weeks) durations, followed by genome-wide TempO-Seq transcriptomic profiling and benchmark dose (BMD) modeling. GenX elicited pronounced non-monotonic mRNA changes in acute exposure conditions, with the greatest number of differentially expressed genes (DEGs) observed at an intermediate concentration (0.4 M). In contrast, chronic exposure exhibited a generally concentration-dependent increase in DEGs, except for the 10 M condition, indicating a more consistent dose-response relationship than acute exposure. Notably, acute and chronic exposures elicited qualitatively distinct mRNA changes with low concordance across matched concentrations, demonstrating that exposure duration was a major determinant of mRNA changes. Acute low-dose GenX exposure preferentially modulated mRNA encoding components of cell cycle-related pathways, whereas acute higher dose exposures suppress mRNA levels of the constituents of lipid metabolic pathways and increase expression of mRNA encoding proteins involved in stress- and toxicity-associated signaling. Chronic exposure revealed a different pattern of changes in mRNA expression not observed under acute exposure conditions, including suppression of cellular components involved in lipid-related pathways at the lowest concentration tested. At higher concentrations, mRNA levels of components of multiple metabolic pathways were altered. Benchmark dose modeling identified a significantly lower transcriptomic point of departure (tPOD) for chronic exposure as compared to acute exposure, suggesting increased cellular sensitivity to prolonged GenX exposure and supporting the relevance of chronic models for human exposure assessment. Collectively, these findings demonstrate that GenX elicits time-dependent and non-monotonic changes in mRNA levels of human liver (HepG2/C3A) spheroids, with distinct responses depending on the exposure duration and dose. This study, therefore, highlights the importance of incorporating chronic, human-relevant in vitro models and transcriptomic endpoints into PFAS risk assessment and suggests that conventional short-term assays may underestimate the biological impact of sustained low-dose exposure. Key message (Impact of the study)This study provides systematic comparisons of short term (4 day) versus longer term (4 weeks), environmentally relevant GenX exposure in human liver spheroids, revealing non-monotonic, time-dependent changes in mRNA levels encoding cellular components of lipid metabolism-related pathways with potential implications for appropriate dose and time exposure parameters for use in New Approach Methods to be applied in risk assessment.

Urban green infrastructure is increasingly promoted as a public-health intervention, yet the biological features that determine exposure to potentially beneficial plant-derived volatile compounds remain poorly understood. Here we quantified airborne terpenes and terpenoids across five contrasting urban greenspaces in Oxford, UK, and related chemical profiles to plant diversity, vegetation structure and surrounding habitat characteristics. Ambient air samples collected across spring and summer were analysed by thermal-desorption gas chromatography-mass spectrometry, alongside field surveys of taxonomic richness, canopy cover, vegetation volume and ground composition. Terpene and terpenoid scentscapes differed strongly among sites and through time, with monoterpenes dominating detected profiles. Sites with greater plant richness and greater vegetation volume below 1.5 m consistently showed higher terpene/terpenoid abundance, whereas total vegetation volume, canopy cover and tree abundance were weaker and less consistent predictors. These relationships were specific to plant-associated chemical classes and were not observed for predominantly anthropogenic volatile compounds. These patterns were resolved across only five independent sampling sites, and the relationships reported here should therefore be considered exploratory. Our findings suggest that human exposure to plant-derived volatiles in cities may be maximised not simply by increasing tree cover, but by designing biodiverse, structurally complex lower-to-mid-storey vegetation within the breathing zone. These results provide an empirical basis for incorporating scentscape ecology into health-oriented urban greenspace design.

Hospital-based wastewater surveillance may complement community and clinical surveillance data in important ways, and may be useful in jurisdictions without community-based wastewater surveillance. From May 2024-April 2026, we analyzed weekly samples (n=190) from three hospitals in New York City using digital PCR to evaluate the sensitivity, specificity, and positive predictive value (PPV) of wastewater viral detection against facility SARS-CoV-2 and influenza A/B inpatient caseloads. Sensitivity was 38-42% for SARS-CoV-2 and 36-49% for influenza A/B, while specificity exceeded 72% for all pathogens. During respiratory seasons, sensitivity reached 81% for SARS-CoV-2 and 81% for influenza A; both had 100% sensitivity during peak case weeks. Notably, off-peak influenza detections occurred in hospital wastewater at all three hospitals in summer 2024 without corresponding hospital case detection, suggesting the presence of undiagnosed cases. These findings underscore the potential utility of hospital-based wastewater monitoring for tracking respiratory virus activity.

Per- and polyfluoroalkyl substances (PFAS) pose significant environmental risks, yet their impact on food crops like legumes remain insufficiently understood. This study investigated the developmental and physiological responses of hydroponically grown mung bean (Vigna radiata) to varying concentrations of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS). High concentrations (1 mM) of PFOA severely impaired early plant development, significantly delaying seed germination, reducing leaf emergence, and suppressing root hair formation compared to PFOS and controls. Over a narrower concentration range (5-500 {micro}M), both compounds caused transient growth stunting at early timepoints (48 h), though plants exhibited partial recovery over time. High-dose exposure (500 {micro}M) significantly decreased seedling wet weights, leaf area, and leaf biomass without affecting dry weights, indicating disrupted water retention and homeostasis rather than reduced biomass accumulation. Spectrophotometric analysis revealed a dose- and compound-dependent effect on photosynthesis, with low-dose PFOA (5 {micro}M) significantly increasing leaf chlorophyll absorbance. Furthermore, quantification of callose deposition revealed that high-dose PFOA (500 {micro}M) and medium-dose PFOS (50 {micro}M) raised baseline immune stress responses, which were not further elevated by subsequent flagellin-22 (flg22) challenge, suggesting a contaminant-induced immune priming mechanism. These findings highlight distinct, chemical-specific toxicological impact of PFAS on legume growth, water dynamics, and defence priming, underscoring critical implications for agricultural productivity and food safety.

Naegleria fowleri is known to be the causative agent of highly aggressive (> 95 % mortality rate) primary amoebic meningoencephalitis (PAM). N. fowleri can colonize drinking water distribution systems (DWDSs) which place additional pressures on water distribution authorities and public health officials. Chlorination and chloramination are widely adopted to combat N. fowleri in DWDSs but this approach is susceptible to failure in certain situations which makes effective N. fowleri surveillance necessary to protect the public from infection. Based on our previous efforts to develop a rapid N. fowleri detection method focusing on the lab-cultured and field-collected samples, this manuscript presents our recent progress investigating an operational DWDS field site seasonally colonized by N. fowleri on a monthly basis over the course of a year using untargeted metabolomics of the entire microbial ecology. A panel of significant features exhibiting changes between N. fowleri positive and negative samples were found and further correlated with the findings from the previous studies. The chemical identities for a subset of the common significant features were confirmed. A new, seasonal prediction model was built based on the common significant features and its performance was compared with our previous efforts. This study illustrates the further development of a rapid N. fowleri detection approach from a longitudinal perspective.

Pesticide use is ubiquitous. While pesticide resistance in target species such as insects is a well-known phenomenon, it is less known how pesticide exposures affect the genetics of non-target species. Here, we demonstrate the research value of integrating existing datasets to study the relationship between chemicals and biodiversity from the genetics perspective by analyzing spatial pesticide concentration data and genetic data from Europe that were not initially generated for toxicological purposes. Specifically, we found associations between environmental pesticide concentrations and genetic variation (i.e., single nucleotide polymorphisms, SNPs) in a non-target species, the wild boar. Gene Ontology (GO) terms and biological signaling pathways related to nervous system function were overrepresented for the impacted genes, especially for insecticides and fungicides. Further, we found that external studies characterizing the molecular mechanisms of these pesticides revealed the same pesticide - GO relationships as those observed in our analysis. Our results show that pesticide-induced genetic changes may not be constrained to target species but may also have an impact on the long-term viability of other wildlife populations. We therefore encourage further research into this area and collaboration across disciplines to develop more comprehensive designated datasets for such analyses. This finding also urges the consideration and inclusion of chemical exposure into conservation protection strategies and greater consideration of genetic impacts from chemicals in environmental risk assessment.

Zoonotic spillover and early human-to-human transmission of emerging viruses are often missed by clinical surveillance. Wastewater surveillance (WS) offers low-cost complementary pathogen detection, but its value for emerging viruses remains uncertain. We reviewed evidence of viral shedding in human waste and combined shedding data, detection models and simulated transmission dynamics into a quantitative framework to identify for which types of emerging viruses WS could add most value. Simulations showed that WS improved probability or speed of outbreak detection for viruses shedding >1/100 to >10 times as much as SARS-CoV-2, depending on probability of clinical symptoms and diagnosis. Value added was highest for transmission scenarios with temporally concentrated infections resulting in spikes in daily shedders. Characteristics of SARS-CoV-2, Mpox, Influenza A, Lassa, and Zaire Ebola viruses appear more favourable for WS than others e.g. chikungunya virus. We anticipate this framework can support more targeted, evidence-based application of WS to emerging threats.

The COVID-19 pandemic remains a global concern, partly due to the rapid mutation rate of SARS-CoV-2 and the emergence of new variants. Wastewater surveillance has proven effective in estimating infection incidence and detecting variants earlier than clinical testing. Its importance has grown as testing rates decline due to milder disease progression. However, current methods typically rely on the prior classification of SARS-CoV-2 lineages or their signature mutations, which may delay detection. We present an alternative method that identifies changes in the viral genetic population over time without requiring prior lineage classification. This population-based approach was applied to sequencing data from wastewater samples, which are generally noisier than clinical samples. We analyzed publicly available sequencing samples from wastewater plants covering Swiss catchments in Altenrhein, St. Gall, Geneva, and Zurich. To address noise, only samples with read depths above 40 and genome coverage of at least 90% were included. Genetic diversity within pooled populations over two time periods was compared to assess changes in viral composition. We demonstrate that SARS-CoV-2 variants can be detected in wastewater sequencing data without prior lineage classification. Our method successfully detected shifts in genetic populations that corresponded to the emergence of known variants of concern (VOCs) in the analyzed regions. Notably, it also revealed the rising prevalence during the first surges of the Omicron variant. Despite the increased noise in wastewater compared to clinical samples, our approach remains effective. However, achieving reliable predictions depends on high sequencing depth, broad genome coverage, and frequent sampling.