Mercury (Hg) pollution has been widely recognized for its severe ecological and health impacts on humans; however, its role in corrosion-related material degradation has received comparatively limited attention. This review examines the mechanisms and risks of mercury-induced corrosion, integrating insights from corrosion science, environmental chemistry, and industrial case studies. It also explores the effects of mercury pollution on industrial corrosion, mercury speciation, surface deposition, environmental cycling of Hg, and corrosion mechanisms, including amalgamation, liquid metal embrittlement (LME), passive film destabilization, and microgalvanic coupling. Finally, the review discusses emerging strategies to mitigate mercury-induced corrosion, including corrosion-resistant materials, protective coatings, mercury-capture technologies, and improved monitoring approaches. By linking corrosion mechanisms to environmental mercury dynamics, this work highlights the importance of integrating materials engineering, environmental risk assessment, and policy frameworks to better manage mercury-related hazards in industrial and environmental systems.
Stream sediments, as long-term sinks for potentially toxic elements (PTEs), provide valuable insights into both natural and anthropogenic contamination. This study presents a comprehensive assessment of PTE contamination, ecological risk, and human health implications across Odisha, eastern India- a region characterized by complex Precambrian geology, intensive agriculture, mining, and industrialization. Concentrations of ten PTEs (Cr, Cd, As, Ni, Cu, Zn, Co, Mn, V, and W) from 28,111 locations collected under the Geological Survey of India NGCM program indicate moderate to very high contamination across the state, with pronounced hotspots in mineralized and industrial belts. Multivariate analyses, including principal component analysis and hierarchical clustering, reveal dominant lithogenic control over Cr, Mn, Ni, Co, Cu, Zn, and V, while anthropogenic enrichment of As, Cd, and W is linked to mining, industrial emissions, and agricultural activities. Non-negative matrix factorization corroborates these source apportionment results. Pollution indices, including enrichment factor, geo-accumulation index, pollution load index, and potential ecological risk index, indicate moderate to high ecological risk in several regions. Human health risk assessment shows that 69.05% of locations exhibit high non-carcinogenic risk (HI > 1) for children, whereas adults show non-carcinogenic and carcinogenic risks in < 0.5% and > 65% of locations, respectively, primarily associated with Cr, Cd, and As. Sobol sensitivity analysis demonstrates that concentration variability predominantly governs carcinogenic risk estimates. Additionally, a machine learning-based framework is developed to classify risk and non-risk zones for both adults and children. This integrated approach provides critical insights for public health protection, targeted remediation, and sustainable land-use planning.
Soil recovery after contamination relies on the surviving microbiota to reconstruct microbial food webs. The ciliate Colpoda aspera and Brevundimonas sp., Rhizobium sp1, Rhizobium sp2 (gram-negative), Bacillus sp1, Bacillus sp2, and Microbacterium sp.(gram-positive) remain active after pulses of light petroleum contamination. We used phase contrast microscopy to assess excystation time and cyst production by C. aspera after placing 65 cysts in petri dishes with 0.5% LNA medium and adding 100 μL of a 5.2 × 108 cell bacterial inoculum from contaminated soil. C. aspera excystation was monitored by triplicate every hour for 72 h. Excystation occurred faster and resulted in a higher number of cysts when fed with gram-negative bacteria, particularly Rhizobium sp2 and Brevundimonas sp. In contrast, C. aspera cysts formed only two daughter cells when fed with Microbacterium sp., reducing the quantity and speed of reproduction. This reproductive behavior may allow other predatory ciliates to coexist when Microbacterium sp. becomes prevalent in a soil hotspot. Ciliates' feeding preferences and nutritional value are required to understand resource partitioning and understanding these interactions can inform strategies to promote resilient microbial communities and accelerate recovery after contamination.
Perfluorooctanoic acid (PFOA) precursors are a class of compounds that are commonly released into the environment through aqueous film-forming foams (AFFFs) and are known to decompose into PFOA. PFOA is one of the most used per- and polyfluoroalkyl substances (PFAS), a class of highly persistent synthetic chemicals. Exposure to PFOA through environmental contamination has been linked to a variety of health concerns, and precursors from AFFFs are sources of PFOA contamination. Although PFOA precursors are often not considered, studies have demonstrated that they contribute to the overall levels of PFOA contamination, meaning that the ability to detect them is important for removing PFOA from the environment. However, the detection of PFOA precursors is limited to mass spectrometry methods, which are expensive and time-consuming. While higher-throughput methods have been developed for PFOA, no high-throughput sensing platforms have been reported for PFOA precursors. To address this problem, we developed a fluorescent sensor platform for detection and differentiation of three specific PFOA precursors, both from each other and from PFOA itself. We demonstrate that dynamic combinatorial libraries (DCLs) made up of dithiol monomers and templated with a solvatochromic fluorophore can be used to form a sensor array that achieves this detection and differentiation at low nanomolar, environmentally relevant concentrations. We can discriminate individual PFOA precursors from each other and perfluoroalkyl carboxylic acids of varying chain lengths, mixtures of varying ratios of the precursor to PFOA, and use our system in complex samples extracted from soil spiked with the precursors. To our knowledge, this is the first report of a fluorescence-based method for the detection and differentiation of PFOA precursors.
This study investigates the occurrence and transfer of potentially toxic metals in roadside and agricultural soils, Pennisetum glaucum fodder, and cow milk across areas with varying traffic density in Kallar Kahar, Pakistan. Samples were digested using a wet acid digestion method and analyzed using Atomic Absorption Spectrometry (AAS) under strict quality control protocols. The analyzed milk samples exhibited a broad range of metal concentrations, with Zn ranging from 1.99 to 3.16 mg/L, Fe from 0.16 to 0.32 mg/L, Mn from 0.02 to 0.28 mg/L, Cu from 0.001 to 0.008 mg/L, Pb from 0.001 to 0.009 mg/L, Cd from 0.0001 to 0.009 mg/L, Co from 0.0002 to 0.008 mg/L, and Mo from 0.001 to 0.004 mg/L. Contamination Factor (CF), Bioconcentration Factor (BCF), Daily Intake of Metal (DIM), and Health Risk Index (HRI) computations suggested that all values are below 1, indicating low levels of contamination and no immediate health risk under the studied conditions. However, values approaching threshold limits (e.g., Cd in milk and Mo in soil) suggest the need for cautious interpretation and long-term monitoring. Comparative analysis with international guidelines confirmed that metal levels in the study area are within safe limits. These findings highlight the suitability of the local environment for fodder production and dairy farming while emphasizing the importance of continuous monitoring to mitigate potential long-term risks.
Fresh water aquifers adjoining the geothermal resources are often vulnerable to trace metal contamination and associated risks to human health. Realistic assessment of health hazard as well as source apportionment play a vital role in designing suitable remedial actions, which can be better achieved through application of probabilistic methods using Monte Carlo Simulations (MCS) and multivariate based Absolute Principal Component Score-Multiple Linear Regression (APCS-MLR) methods. In this study, a comprehensive analysis of groundwater quality was performed using multiple pollution indices (HPI, HEI, Cd, IWPI), MCS and APCS-MLR methods. Chemical results indicate that TDS, F- and NO3- showed exceedances in 19%, 38% and 23% of the samples respectively while trace metals (Fe, Mn, Pb, and As) showed higher exceedances compared to WHO limits. Pollution indices suggest that 73% of the samples fall under low contamination and the rest (27%) in high risk category. MCS infers both non-carcinogenic and carcinogenic health risks to different age groups mainly due to arsenic and lead. Sensitivity analysis indicates body weight, ingestion rate as most influential followed by arsenic concentration. High geochemical mobility is noticed for Zn and Co while Al and Ni are largely immobile. Both relative mobility index and APCS-MLR model output point to rock weathering and geothermal sources as the key contributors accounting for 19.8% of the trace metal load in this region. This integrative approach underscores the need for regular monitoring and implementation of policies for safeguarding public health in this region.
Sea salt increasingly harbors organic contaminants from personal care products, yet current monitoring methods lack spatial resolution and require destructive sampling. This study introduces an innovative analytical framework integrating Laser-Induced Fluorescence (LIF) Hyperspectral Imaging (HSI) with machine learning for the rapid, non-destructive detection of sunscreen residues on salt crystals. To simulate contamination, seawater from the Mediterranean coast (Alexandria, Egypt) was spiked to achieve a 10 mg/L sunscreen concentration within the seawater matrix prior to crystallization; this formulation contained Ethylhexyl Methoxycinnamate, Homosalate, and Ethylhexyl Salicylate. A SOC710 HS camera (128 bands) acquired fluorescence data under 450 nm laser excitation. Raw data underwent preprocessing and dimensionality reduction via Sparse Principal Component Analysis (Sparse PCA, λ = 0.5, k = 4 components, 73.4% sparsity). A Support Vector Machine (SVM) with an RBF kernel was trained on these sparse features. Performance evaluation employed tenfold stratified cross-validation, an 80-20 holdout test on ROI-based spectra, and independent sample validation against manually annotated pixel-wise ground-truth masks. While ROI-based tests yielded near-perfect accuracy under ideal conditions, full-image evaluation achieved ≈96% pixel-wise accuracy (precision ≈ 0.99, recall ≈ 0.95, F1 ≈ 0.97), providing a realistic estimate under heterogeneous conditions. Full-image classification mapped widespread contamination (57.8% of pixels), whereas an independently prepared clean salt sample produced zero false positives. The integrated Sparse PCA-SVM framework transforms fluorescence-imaging data into spatio-chemical maps, simultaneously revealing contaminant presence and spatial distribution on salt surfaces, thereby offering a powerful paradigm for the interpretable monitoring of organic pollutants in food materials.
The contamination of aquatic environments by pharmaceutical residues, notably paracetamol (PCT), has emerged as a significant environmental issue, attributed to its persistence and the inadequate efficacy of traditional treatment approaches in its removal. In this study, TiO2/biochar composite photocatalysts were synthesized via an ultrasonic-assisted wet impregnation method and applied for the photocatalytic degradation of PCT under UV light irradiation. Biochar was produced from rice straw biomass waste through a controlled pyrolysis process and subsequently composited with anatase-phase TiO2 at biochar mass ratios of 10, 20, and 30 wt.%. The use of rice straw-derived biochar not only supports agricultural waste valorization but also provides a porous carbon matrix that enhances TiO2 dispersion and surface properties. The photocatalysts were characterized using XRD, FTIR, BET, FESEM-EDX, XPS, PL, and UV-DRS. XRD analysis confirmed the preservation of the anatase TiO2 phase with crystallinity 93.92% and crystallite sizes of 40-50 nm. FTIR spectra revealed characteristic Ti-O-Ti and O-H vibrations, along with organic functional groups associated with biochar. BET results demonstrated an increase in surface area and pore volume for the TiO2/biochar composites compared to pristine TiO2, while FESEM images showed well-dispersed nanoscale particles (< 100 nm). UV-DRS analysis indicated band gap energies in the range of 3.1-3.2 eV. Photocatalytic experiments showed that the TiO2/biochar composite containing 20 wt.% rice straw-derived biochar exhibited the highest PCT degradation efficiency, achieving 94% removal within 180 min at an initial concentration of 10 mg/L. Moreover, the composite photocatalyst demonstrated good stability, maintaining degradation efficiencies of 91-94% over repeated reuse cycles. The findings underscore the efficacy of biochar derived from rice straw in modifying TiO2, positioning it as a promising and sustainable photocatalyst for the treatment of pharmaceutical wastewater.
Access to safe drinking water remains a critical public health challenge in many parts of rural India. People's perceptions of water quality, often based on sensory cues, may not align with laboratory evidence, leading to gaps in protective behaviour. This study examines the divergence between perceived and measured water quality in a southern district of West Bengal. A mixed-method study was conducted in four villages of North 24 Parganas. The villages were selected based on computed Water Quality Index based on government data, and the study followed a comparative cross-sectional design. Quantitative data were collected from 521 individuals across 120 households via a semi-structured questionnaire on background characteristics, water sources, water related perceptions treatment practices, and reported health outcomes. Household water samples were tested in a science laboratory to measure physicochemical and microbial parameters. Quantitative analysis included univariate and bivariate statistics and logistic regression, while 16 in-depth interviews explored water related perceptions, health experiences, and willingness to pay for safe water. Laboratory analysis showed that 64% of the households consumed poor-quality drinking water, with fluoride (76%) and arsenic (65%) exceeding permissible limits. A clear perception-measured gap was observed, confirmed by McNemar's test (χ² = 12.25, p < 0.001). Misperception was higher among households with limited awareness of contamination, lack of treatment practices, and greater distance from water sources. Health risks were diverse, including self-reported gastrointestinal illnesses and respiratory symptoms. While many households expressed willingness to pay USD 0.16 to USD 3.20 per month for safe drinking water, affordability remained a barrier for many households. There is an urgent need for context-specific risk communication, continuous water quality monitoring and displaying such levels, and providing affordable and safe water delivery systems in rural West Bengal.
Groundwater fluoride contamination in Tamil Nadu's geochemically diverse aquifers necessitates high-fidelity, cost-effective monitoring. This study introduces a Geochemically-Aware Domain Adaptation (GADA) framework to predict fluoride concentrations in data-scarce regions.Query Using 2089 data samples from 32 districts of Tamilnadu collected from Central Ground Water Board, India, different domain adaptation models like Best Source Transfer (BST), Correlation Alignment (CORAL), and Feature-Weighted Data Augmentation (FWDA) strategy utilizing Gradient Boosting as a base estimator is developed. While direct model transfer showed poor performance, the GADA achieved a robust R2of 0.91 with a minimal standard deviation of 0.042, an MSE of 0.015, and an MAE of 0.094. Functioning as a Virtual Sensor, the model performs real-time inference using only three low-cost parameters: pH, Total Dissolved Solids (TDS), and Electrical Conductivity (EC). Field validation against Ion-Selective Electrode (ISE) measurements confirmed the system's high predictive fidelity. This stable and accurate solution provides a scalable tool for continuous environmental monitoring and decentralized water governance in heterogeneous hydrogeological domains.
Accurate regional mapping of soil heavy metals is increasingly supported by multi-source environmental covariates, yet predictive performance is often limited by sparse field sampling that cannot capture regional heterogeneity. We developed DLTL, a novel deep learning framework that integrates kriging-based virtual sample augmentation with transfer learning to improve mapping under limited observations. For six metals (Zn, Cu, Cr, Cd, Pb, and As) in the Yangtze River Delta, China, DLTL outperformed benchmark models, improving R2 by 17.36-42.99% over an augmented deep learning baseline, 24.00-95.34% over ordinary kriging (OK), and 34.50-133.93% over random forest (RF). Optimal performance was achieved with 6-km virtual sampling, full-network fine-tuning, and terminal-layer replacement. The shapley additive explanations (SHAP) analysis revealed that soil properties (37-42%) and climate (23-32%) dominated model explanations, with element-specific contributions from anthropogenic indicators and PM2.5. The resulting 1-km resolution maps better delineated localized hotspots, identifying a larger fraction of high ecological-risk areas (3.20% vs 0.07% for RF) while reducing false-positive exceedance of childhood carcinogenic risk (0.09% vs 1.50% for OK). DLTL provides a scalable solution for regional contamination mapping and risk screening in covariate-rich but sample-poor settings.
Potentially toxic trace elements (PTTEs) pose a risk to living organisms. We used honey bees (Apis mellifera) to explore differences in PTTE contamination levels between two study sites. Two apiaries with five bee colonies each were studied: The experimental apiary was located at a former waste deposit site (Witzwil; Switzerland), and the control apiary was 4.5 km away in the neighbouring area (Bellechasse; Switzerland). Pollen was collected from colonies from May to August 2022 and 2023, and we developed an analytical method to assess 22 PTTEs. We quantified 19 PTTEs in at least one of the pollen samples (n = 80), with maximal levels recorded for Mn (298.8 mg/kg), B (95.1 mg/kg), Zn (63.4 mg/kg), Cu (19.2 mg/kg), Rb (17.7 mg/kg), Ba (11.1 mg/kg), and Sr (3.2 mg/kg). Most notably, site-specific and seasonal variations were observed. For example, in June, pollen at the Witzwil site had statistically significant higher average concentrations of PTTEs-Mn (204.6 ± 53.1 mg/kg), Rb (13.9 ± 2.3 mg/kg), Ba (6.7 ± 2.2 mg/kg), and Ni (1.8 ± 0.4 mg/kg)-than the Bellechasse apiary, with Mn (74.2 ± 67.1 mg/kg), Rb (5.6 ± 2.0 mg/kg), Ba (4.4 ± 2.5 mg/kg), and Ni (1.1 ± 0.5 mg/kg). By contrast, the levels of several PTTEs (e.g., Mn, Ba, and Ni) were similar in July and August in both apiaries. For maximal Cu, Cd, Cr levels in pollen, we expect no increased acute oral toxicity to adult honey bees above the expected mortality levels.
Bacteriophages in natural environments play a critical role in microbial ecology by regulating bacterial populations, mediating nutrient cycling, and facilitating horizontal gene transfer. Aquaculture operations, particularly inland fish farms, are major sources of anthropogenic influence on freshwater ecosystems. Here, we present three viral metagenomic datasets derived from freshwater samples collected at an inland aquaculture effluent site and adjacent upstream and downstream locations along the Sung-am River in Jincheon County, South Korea. The datasets were generated using the Illumina HiSeq X sequencing platform, yielding approximately 10.0-11.2 Gbp per sample. Quality assessments confirmed minimal bacterial contamination, with negligible proportions of rRNA and bacterial marker genes. Assembly using metaSPAdes and MEGAHIT, application of Phables to resolve high-quality phage genomes (viral metagenome-assembled genomes; vMAGs), viral identification with VirSorter2, and clustering using Vclust, resulted in 2,837-3,156 virus operational taxonomic units (vOTUs; ≥10 kb) per sample. Each vOTU sequence is analyzed for taxonomic assignment and putative host prediction. These datasets provide a valuable resource for further studies on viral diversity and microbial ecology in freshwater ecosystems affected by aquaculture.
Craniofacial wounds present unique management challenges owing to the aesthetic significance of the facial region, proximity to vital structures, risk of contamination from oral flora, and the frequent presence of exposed bone or hardware. Manuka honey, derived from the Leptospermum scoparium plant, possesses well-documented antimicrobial, anti-inflammatory, and wound healing properties attributable primarily to its methylglyoxal content, osmotic activity, and low pH. However, no review has specifically addressed its application in the craniofacial context. A narrative review was conducted using PubMed, Scopus, and Web of Science databases. Search terms combined honey-related keywords with craniofacial and head-and-neck terminology. Clinical studies, case reports, randomized controlled trials, and relevant general wound care reviews were included. The Scale for the Assessment of Narrative Review Articles (SANRA) was used as a quality framework. Evidence supporting the use of Manuka honey in the craniofacial region was identified across several wound categories, including scalp defects with exposed calvarium, head and neck oncologic reconstruction wounds, oral and maxillofacial infections, partial flap necrosis, facial surgical wounds, and burns. In vitro data also suggest selective cytotoxicity against tumor cells, raising the possibility of a dual wound healing and antitumor role in postoncologic surgical wounds. Most available evidence remains at the level of case reports and small series, with only one randomized controlled trial conducted specifically in head and neck wounds. Manuka honey represents a safe, cost-effective, and promising adjunctive wound care modality for the craniofacial surgeon. Registered medical-grade products are ideal where available, but UMF-certified commercial Manuka honey with verified antimicrobial ratings offers a scientifically rational alternative in regions where medical-grade products are not accessible. Prospective studies evaluating Manuka honey in specific craniofacial wound types are warranted.
High-energy gunshot injuries to the distal humerus frequently result in extensive comminution, severe soft-tissue damage, and contamination, making definitive fixation both technically demanding and biologically challenging. During staged management with temporary stabilization, extra-articular callus formation may occur prior to definitive fixation, potentially influencing the surgical decision to preserve or excise this tissue. This study aimed to evaluate the clinical and radiological outcomes of a fixation strategy that preserves extra-articular callus in high-energy distal humerus fractures caused by gunshot injuries. This retrospective study included 21 male patients with Gustilo-Anderson type IIIA distal humerus fractures caused by high-velocity gunshot injuries, treated between 2016 and 2024. All patients initially underwent temporary stabilization followed by definitive fixation. Patients were stratified according to whether the extra-articular callus tissue was preserved (n=9) or excised (n=12) during surgery. Functional outcomes were assessed using the Disabilities of the Arm, Shoulder and Hand (DASH) score and the Mayo Elbow Performance Index (MEPI), and radiographic union time was recorded. The mean patient age was 28 years (range, 22-43). According to the AO/OTA (Arbeitsgemeinschaft für Osteosynthe-sefragen/Orthopaedic Trauma Association) classification system, 81% of fractures were type 13C3. Nerve injury was present in five patients (23.8%), and heterotopic ossification developed in five patients (23.8%). No significant intergroup differences were observed in DASH scores, MEPI scores, range of motion, or infection rates (all p>0.05). However, union time was significantly shorter in the callus-preserved group compared with the excision group (18.0±3.1 vs. 23.5±3.3 weeks, p=0.004). Nerve injury (p=0.043) and heterotopic ossification (p=0.025) were associated with higher DASH scores, indicating poorer functional outcomes. A callus-preserving fixation approach may offer a biological advantage in the management of high-energy distal humerus gunshot fractures by promoting earlier bone healing without compromising functional outcomes. When extra-articular callus does not interfere with anatomical reduction, preserving it in situ may be considered as part of a staged damage-control-to-definitive fixation strategy.
Affordable and sustainable water purification and reuse remain a global challenge for decentralized systems. The release of untreated or insufficiently treated grey and wastewater into surface waters contributes to pollution and increases downstream treatment costs due to nutrients, organic matter, heavy metals, and microbial contamination. Hybrid approaches combining biological and physicochemical processes are emerging, yet modular systems enabling direct integration of living plant roots with functional biopolymer-based filters remain underexplored. Here we demonstrate a modular co-filter system integrating plant roots with biopolymer filters enabling effective decentralized greywater treatment within flexibly connectable pot units. The combination of Sparganium erectum with cellulose-chitosan (CC) filters, including copper-functionalized variants (CCC) was evaluated using synthetic greywater under laboratory conditions. The co-filter achieved substantial reductions in organic matter, nutrients, turbidity, and microbial indicators. CCC filters exhibited enhanced antibacterial activity against Escherichia coli via copper release, whereas CC filters had limited antimicrobial effects. The plants tolerated metal-containing greywater and contributed to nutrient and organic matter removal without adverse effects on plant biomass. Treatment performance improved with increasing system complexity. These results demonstrate the feasibility of a modular, nature-based co-filter concept as an approach for decentralized greywater treatment and water reuse. This study presents a novel laboratory-scale proof-of-concept for decentralized greywater treatment using a modular co-filter system that integrates biotic and abiotic filtration mechanisms. The work builds upon previously developed chitosan–cellulose (CC) filters and extends their functionality through copper incorporation (CCC filters) to enhance antibacterial performance, without claiming controlled or optimized copper release. A key innovation is the direct integration of living roots of Sparganium erectum within the CC-based filter, enabling combined treatment of organic matter (COD/TOC), nutrients, selected metals (Cu), and microbial indicators in a compact, modular setup. This study demonstrates the feasibility and potential synergy between plant-root-based processes and regenerable adsorption filters in a flexibly connectable pot system under controlled laboratory conditions. The modular design allows parallel or sequential configurations, offering adaptability for future scaling and optimization. Overall, the study provides experimental evidence supporting the integration of biotic and abiotic components for decentralized greywater treatment and lays a foundation for future pilot-scale and long-term studies.
Global ecosystems are rapidly changing under human pressures such as land-use change, degradation, and trace metal pollution. These conditions often favor invasive plants, yet the links between invasiveness and metal contamination remain insufficiently understood. This study aimed to compare the biogeochemical responses of a native species (Tanacetum vulgare) and an invasive species (Solidago gigantea). Specifically, their capacity for metal uptake and translocation was investigated to assess whether certain traits may facilitate the performance of invasive plants in contaminated sites. Concentrations of Cd, Cr, Cu, Pb, Zn, Ni, Fe, and Mn were determined in soils and in the roots and aboveground organs of both species sampled in areas with and without industrial impact. The results showed that both species are capable of inhabiting anthropogenically altered and metal-contaminated sites. Importantly, they both exhibited reduced uptake of metals in polluted soils, indicating the utilization of a metal-excluder strategy. T. vulgare was more likely to restrict metal uptake at the root level, whereas S. gigantea appeared to limit metal translocation to aboveground parts. Moreover, S. gigantea contained significantly lower levels of Cd, Ni, and Pb in its organs than T. vulgare, suggesting greater efficiency in avoiding metal accumulation. These findings support the classification of both species as excluders and highlight the adaptive capacity of invasive species in disturbed environments.
Eutrophication caused by excessive nutrient discharge has led to the frequent occurrence of cyanobacterial blooms, during which toxic metabolites such as microcystins (MCs) are released into aquatic environments. Among these, microcystin-LR (MC-LR) is the most widespread and toxic congener, posing serious threats to both ecological safety and human health. In this study, a novel bifunctional detection probe (A2.3-AP) was developed by genetically fusing a MC-LR-specific nanobody (A2.3) with alkaline phosphatase (AP) via a flexible (GGGGS)3 linker. The A2.3-AP bifunctional detection probe integrates antigen recognition and enzymatic catalysis within a single molecule, thereby simplifying the immunoassay procedure and improving detection performance. Based on this bifunctional probe, a one-step indirect competitive enzyme-linked immunosorbent assay (IC-ELISA) was established for the rapid and sensitive determination of MC-LR. Compared with conventional ELISA, the proposed method reduced the assay time by approximately one hour and improved the detection sensitivity threefold, achieving a detection limit of 12.47 ng mL-1. Lake water samples were used to verify the matrix tolerance of the assay, and spiked samples were cross-validated by HPLC to confirm its accuracy. The A2.3-AP based immunoassay provides a high-performance analytical tool for the prevention and control of MC-LR contamination events and offers a new approach for improving traditional enzyme-linked immunoassay methods.
Water samples from seven Matagorda Bay locations were collected in spring, summer, and fall to assess micro- and nano-plastics contamination. Samples were oxidatively digested (30% H2O2), filtered, dried, and analyzed by Fourier Transform Infrared spectroscopy FT-IR ATR, Raman spectroscopy, Differential Scanning Calorimetry DSC, and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy SEM-EDS. The identification of micro- and nano-plastics in estuarine waters is complicated by high salinity and inorganic matrices that can obscure or mask polymeric signals. To address this challenge, an integrated analytical approach was employed, combining vibrational spectroscopy, thermal analysis, and electron microscopy to compensate for the limitations of individual techniques. While surface-sensitive and element-specific methods were influenced by salt encapsulation, differential scanning calorimetry provided complementary bulk thermal evidence of polymeric materials embedded within the inorganic matrix. The spectra consistently showed peaks at ∼3300, 1630, and 1100 cm-1, indicating amine and hydrocarbon groups associated with synthetic polymers. The thermograms of DSC for fall and summer revealed three melting transitions (∼105-110 °C, ∼150 °C, ∼220 °C), consistent with polyethylene PE, polypropylene PP, polyvinyl chloride PVC, and high-melting polyamides PA or polystyrene PS. By contrast, spring samples showed only two transitions (∼85-95 °C, 140-150 °C), suggesting absence of some micro/nano-plastic materials. The outcomes of SEM-EDS demonstrated that the dried residues were dominated by inorganic salts (sodium Na, magnesium Mg, calcium Ca, sulfur S, chlorine Cl) with little detectable carbon, implying micro- and nano-plastic particles were embedded in a salt matrix. Overall, the data suggests the presence of common plastics (PE, PP, PVC, PA) in Matagorda Bay waters, with possible seasonal variation. The prevalent salt background highlights analytical challenges in detecting plastics in estuarine samples. Combining DSC technique alongside SEM-EDS and FT-IR show micro/nano-plastic particles encapsulation within inorganic salt. These findings underscore the plastic pollution in this coastal system and the need for rigorous monitoring and improved isolation of microplastics from saline matrices.
Seasonal freeze-thaw process critically regulates arsenic (As)-metabolizing microorganisms (AMMs) in lake sediments through redox-nutrient dynamics. However, the current understanding of microbially mediated As transformation and mobilization processes under freeze-thaw dynamics remains poorly constrained. This study systematically investigated the successional patterns and driving mechanisms of As-metabolizing functional genes and microbial community structures of AMMs in lake sediments during the freeze-thaw process. This study focused on Lake Wuliangsuhai-a typical mid-high latitude lake in northern China-and employed an integrated framework of co-occurrence networks, Mantel tests, and correlation heatmaps. The results revealed that freeze-thaw processes drive significant AMMs restructuring, altering taxonomic composition and functional gene expression while controlling As environmental fate through regulating microbial metabolic functions, altering redox regimes, and restructuring community interaction networks. Co-occurrence network revealed stage-specific restructuring of microbial interactions during freeze-thaw process: robust mutualism established foundational networks during the pre-freezing stage; simplified modularity reflected functional differentiation during the ice-covered period; post-thaw modularity increased during structural reorganization; and synergistic complexity characterized adaptive strategies during the open-water period. Integrated results from Mantel tests and correlation heatmaps identified total nitrogen (TN), total phosphorus (TP), Fe(II), As(III), and As(V) as key succession drivers, with stage-dependent influences on AMMs. This work elucidates fundamental regulatory mechanisms through which seasonal freeze-thaw processes govern As-metabolizing gene dynamics and microbial ecological functions in lake sediments. It further highlights how microbially driven As transformations exacerbate sedimentary contamination risks under climate change, providing critical theoretical foundations for regional water management and pollution mitigation strategies.IMPORTANCESeasonal freeze-thaw processes in cold lakes dramatically control arsenic pollution risks, but how microbes drive this process remains a critical knowledge gap. This study reveals how winter ice cover and spring thaw create "hot moments" for toxic arsenic release by activating specialized sediment microbes, necessitating stage-specific water quality management. Crucially, nutrient loading (total nitrogen/total phosphorus) exacerbates arsenic (As) transformations by stimulating functional gene expression and microbial interactions. As climate change shortens ice seasons, these contamination pulses may become more frequent and severe. By identifying key microbial indicators and high-risk transition periods, our findings empower lake managers to predict arsenic hazards. This science is vital for safeguarding freshwater ecosystems and human health across ice-affected regions worldwide.