Persistent toxic substances (PTS), including heavy metals, persistent organic pollutants (POPs), and persistent, mobile, and toxic/very persistent and very mobile (PMT/vPvM) substances present an increasing menace to soil health, alimentary systems, atmospheric cleanliness as well as human health. Despite the large amount of literature on each of the individual groups of contaminants, there is still no unified model that connects the dynamics of the soil-atmosphere environment, bioaccumulation in the food chain, new detection techniques, and policy measures. This review presents an interdisciplinary synthesis of dynamics in the PTS in the agricultural environment, explicitly incorporating (i) historic contaminants and emerging PMT/vPvM chemicals, (ii) soil-crop-livestock-human transfer pathways, and (iii) the state-of-the-art remediation and monitoring technologies into a single management framework. We critically evaluated conventional remediation methods alongside next-generation methods, such as engineered consortia of microorganisms, synergistic phytotransformation of plants and microbes, biochar-assisted immobilization, nanosensor-based detection, IoT-based soil sensing, precision agriculture, machine-learning-driven risk prediction, and blockchain-based traceability. Contrary to the previous reviews, which only take into account the remediation, detection, and policy separately, this study presents a systems-based approach, which integrates technological innovation, sustainable agronomic practices, and multilayered governance tools (such as the Stockholm Convention, REACH, and national soil action plans). We highlight the fact that the combination of smart agricultural technology and regenerative land management will help reduce the accumulation of PTS and maintain productivity, especially in resource-scarcity settings. The review outlines the research gaps, including contaminant-microbiome interactions, longitudinal deterioration of ecosystem services, and socioeconomic barriers to technology adoption. We propose a transdisciplinary roadmap that aligns environmental toxicology, soil science, public health, and policy innovation to mitigate PTS and safeguard food security. This integrative approach provides a strategic framework for advancing sustainable management of persistent toxic substances in agricultural systems. This study looks at persistent toxic substances (PTS), harmful chemicals like some pesticides, industrial pollutants, and heavy metals that do not easily break down in the environment. Because they linger in soil, water, air, and food, they can move through the food chain and affect both ecosystems and people.In this study, the authors reviewed recent research and real-world cases to explain where PTS come from (e.g., farming chemicals, industrial waste, plastics), how they spread (air, water, and soil), and what health problems they can cause (such as hormone disruption, breathing issues, nerve damage, and cancer). They also examined solutions, from traditional cleanup methods to newer, nature-based options.
Treatment wetlands are widely used for greywater treatment in Europe, but upcoming stricter nutrient limits in the revised EU Urban Wastewater Treatment Directive (EU 2024/3019) raise questions about their ability to meet future standards. This is especially relevant as interest increases in scaling systems beyond 1,000 PE and in reusing treated greywater, which under the EU Water Reuse Regulation (EU 2020/741) requires compliance with EU 2024/3019 effluent limits. To assess performance under these conditions, four greywater treatment wetlands and one mixed wastewater reference wetland were monitored for 18 months. All wetlands consistently produced dissolved COD below 50 mg/L, within the strictest limit of 125 mg COD/L. However, only three of the wetlands achieved total nitrogen concentrations below the required 6 mg N/L. Regarding total phosphorus, only the two wetlands, which used phosphorus adsorbing media, met the 0.5 mg P/L limit. Performance was not strongly linked to flow path design. Instead, lower nitrogen loading and use of phosphorus adsorbing media were associated with higher quality effluents. Other factors, including system age and groundwater interactions, showed no consistent influence across sites. Overall, results show that treatment wetlands can meet EU wastewater requirements for greywater, though nutrient removal may require targeted design strategies.
To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R2) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m2). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m2) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m2) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region. ［摘要］ 目的 采用机器学习方法分析长江三角洲地区钉螺密度的影响因素, 并识别关键环境因子, 为钉螺精准控制提 供参考。方法 在中国疾病预防控制中心寄生虫病防治信息管理系统中, 获取2011—2021年长江三角洲 (上海市、江苏 省、浙江省和安徽省) 以行政村为单位的钉螺调查数据。于谷歌地球引擎网站获取研究区域海拔、坡度、地形、归一化植 被指数 (normalized difference vegetation index, NDVI)、植被类型、土壤类型, 总石油烃 (total petroleum hydrocarbon, TPH)、铵态氮、无机氮、溶解氧含量, 水体pH值、化学需氧量 (chemical oxygen demand, COD)、无机磷含量等环境因子数据; 于哥 白尼气候数据存储库获取研究区域年降水量、干旱指数和年均温度 (annual mean temperature, AMT) 等气候因子数据。将 2011—2021年长江三角洲地区钉螺调查数据随机分为训练集 (占70%) 与测试集 (占30%), 基于R 4.3.0软件, 选取随机 森林 (random forest, RF)、极端梯度提升 (eXtreme gradient boosting, XGBoost)、支持向量机 (support vector machine, SVM)、梯度提升机 (gradient boosting machine, GBM) 和神经网络 (neural network, NN) 模型进行钉螺密度模型构建与对比分析。采用XGBoost模型构建钉螺密度预测模型, 量化各环境因子对钉螺分布的影响程度。计算沙普利加性解释 (SHapley Additive exPlanations, SHAPs) 值, 估计各变量对模型预测结果的平均贡献度, 筛选影响钉螺种群密度的核心环境因子。结果 5种机器学习模型中, XGBoost模型决定系数、均方误差、均方根误差和平均绝对误差分别为0.855、0.188、0.434和 0.155, 综合评价结果最优。基于XGBoost模型分析钉螺密度影响因素, 16种环境因子中, SHAPs值排序居前4位的为年 降水量、海拔、干旱指数和NDVI, 累计SHAPs值贡献度为75%, 高于其他环境因子。当NDVI > 0.6时, 钉螺密度随NDVI 值升高而增加, 并于NDVI为0.8时达峰值 (1.60只/0.1 m2)。当海拔处于14 ~ 40 m时, 钉螺密度随海拔升高而增加。当年 降水量为900 ~ 1 300 mm时, 钉螺密度缓慢上升; 年降水量为1 300 ~ 1 500 mm时, 密度迅速增高至峰值 (1.52只/0.1 m2)。当干旱指数在0.8 ~ 1.1时, 钉螺密度迅速增高至峰值 (1.60只/0.1 m2); 当干旱指数> 1.1时, 钉螺密度逐渐降低。结论 XGBoost模型在长江三角洲地区钉螺密度预测与关键环境因子识别中应用效果较优。年降水量、海拔、干旱指数和 NDVI是影响该地区钉螺分布与密度的关键环境因子。.
A 56-day feeding trial was conducted to investigate the effects of replacing fishmeal with Periplaneta americana meal (PAM) on the growth performance, liver health, and intestinal microbiota of largemouth bass, Micropterus salmoides. A total of 450 fish (initial body weight 14.55 ± 0.09 g) were randomly divided into 5 groups, with 3 replicates in each group and 30 fish per replicate. Five diets were formulated to replace fishmeal with PAM at the rate of 0% (control group, P0), 15% (P15), 30% (P30), 45% (P45), and 60% (P60). The results showed that PAM substitution in the diets did not significantly affect the specific growth rate (SGR) and weight gain rate (WGR) in P30 and P45 (P > 0.05). The L* and water holding capacity (WHC) of muscle in all PAM groups were higher than those in P0 (P < 0.05). In P15 and P30, the activities of SOD, GPX, T-AOC, and CAT in largemouth bass liver were significantly increased (P < 0.05). 16S rRNA analysis indicated that replacing fishmeal with PAM caused changes in intestinal microbiota. Compared with P0, there were no significant differences in the relative abundances of Firmicutes and Proteobacteria in P15 and P30 (P > 0.05), while the relative abundances of Fusobacteriota and Actinobacteriota were significantly reduced (P < 0.05). However, the abundances of Firmicutes, Proteobacteria, Actinobacteriota, and Verrucomicrobiota were significantly decreased in P45 and P60, while the relative abundance of Fusobacteriota was significantly increased (P < 0.05). In P0, P15, and P30, the abundance of Mycoplasma, Pseudomonas, Bradyrhizobium, and Citrobacter significantly increased, while in P60, the abundance of Plesiomonas, Cetobacterium, and Aeromonas significantly increased, and the abundance of Mycoplasma, Pseudomonas, and Akkermansia significantly decreased (P < 0.05). In conclusion, up to 30% fishmeal can be replaced by PAM in the diet without adversely affecting the growth performance and improving the muscle quality and liver antioxidant capacity of largemouth bass. However, replacing more than 30% of fishmeal with PAM may cause liver tissue damage and affect the composition of intestinal microbiota of largemouth bass. This study will provide practical strategies for the substitution and application of PAM in aquafeeds and for improving the muscle quality of largemouth bass.
Glyoxalase-I (GLO-I) is a zinc-dependent metalloenzyme and a promising target for anticancer drug discovery. It catalyzes the detoxification of methylglyoxal, a cytotoxic byproduct of glycolysis, a metabolic shift commonly observed in cancer cells. GLO-I overexpression in tumor cells promotes multidrug resistance and tumor progression. However, the role of conserved water molecules within the GLO-I active site remains insufficiently explored, and understanding their influence on ligand binding may improve structure-based inhibitor design. This study aimed to identify potential GLO-I inhibitors by examining the effect of conserved active site water molecules on ligand binding and activity predictions using a structure-based drug design approach. Three human GLO-I crystal structures were used to generate structure-based pharmacophore models under two conditions: with and without crystallographic active site water molecules. The models were applied to virtually screen the OTAVA Lead-Like library (commercial lead-like compound library). Molecular docking of the resulting hits was then performed under both hydration conditions to evaluate effects on ligand binding affinity and pose orientation. Top-ranked compounds were purchased and evaluated in vitro for GLO-I inhibition. The most active hit was further evaluated by 1000 ns molecular dynamics (MD) simulations (± crystallographic waters), including analysis of pose stability and binding-site water behavior. Among the 22 compounds tested in vitro, five showed inhibitory activity, with IC50 values ranging from 12.07 to 25.36 μM. The most potent compound (hit 19) demonstrated an IC50 of 12.07 ± 0.31 μM and 85.63% inhibition at 50 μM. Docking analysis indicated that including crystallographic water molecules often increased docking scores but could distort binding orientations, whereas docking without conserved active site water molecules more consistently produced plausible poses and better agreement with experimental activity trends. For GLO-I, docking without conserved active site water molecules provided more accurate results and may represent a more reliable approach for studying ligand binding and guiding inhibitor design.
Sulfonamides (SAs) are frequently detected in natural water bodies, sediments, and wastewater treatment plants (WWTPs). Their persistence in the environment induces the generation and dissemination of antibiotic resistance genes (ARGs) as well as drug-resistant bacteria, posing threats to ecosystems and public health. Current processes are insufficient for the removal of SAs. This paper reviews the recent research progress in SAs in terms of the occurrence concentrations, biological toxicity, and induction of resistance gene transfer, as well as our preliminary work on the degradation technology and mechanisms of SAs. Through the review, this paper summarizes the pollution status, hazards, biodegradation processes and key influencing factors of SAs, clarifies the roles of biological community interactions, microbial co-metabolism, eukaryotic enzymatic degradation, and interactions between gut microbiota and the host in the degradation of SAs and horizontal transfer control process of ARGs, and outlines representative degradation pathways, degradation kinetics, and related research methods. Furthermore, this paper makes an outlook on the future research directions from the aspects of innovative combination process, multi-factor synergistic influencing mechanisms, and mutually beneficial cooperation between eukaryotes and their microbial communities, aiming to provide insights for deciphering the degradation mechanisms of SAs and formulating pollution control measures. 磺胺类抗生素(sulfonamides, SAs)在自然水体、沉积物和污水处理厂中检出率高，长期存在会诱导抗性基因和耐药菌的产生和传播，对生态系统和公共健康构成威胁。我国城镇污水处理厂现有工艺难以实现对SAs的有效削减。本文基于近年来国内外学者在SAs检出浓度、生物毒性、诱导抗性基因转移等方面的研究进展，结合本课题组开展的SAs降解技术与机制研究方面的工作，总结了污水中SAs的污染现状和危害、生物降解工艺、关键影响因素，阐明了生物群落协作、微生物共代谢、真核生物酶解、肠道菌群与宿主互作等在SAs降解和抗性基因(antibiotic resistance genes, ARGs)水平转移控制过程中的作用原理，梳理了代表性SAs的降解路径、降解动力学和相关研究方法，并从组合工艺创新、多因素协同影响机制、真核生物及其微生物组互利协作等方面对未来研究方向进行了展望，为SAs降解机理的深入研究和污染治理提供参考。.
Extensive prescription and consumption of non-steroidal anti-inflammatory drugs (NSAIDs) in humans and livestock medicines lead to their constant discharge into the natural waters posing deleterious ecological and health concerns. Considering their existence in water as anions, a new adsorbent containing a large proportion of quaternary ammonium groups for anion-exchange micro-magnetic solid phase extraction (AE-µ-MSPE) was designed and synthesized by grafting G2.0 of the poly(amidoamine) dendrimers (G2.0PAMAM) onto the magnetic carbon nanotubes (MCNTs) followed by quaternization with glycidol. After successful characterization by NMR, FT-IR, XPS, SEM, TEM, EDX, XRD, VSM, and TGA, the synthesized adsorbent QPAMAM@MCNTs in combination with HPLC-UV was applied for the preconcentration and determination of four NSAIDs in environmental waters. Extraction parameters were optimized using Box-Behnken design (BBD), while desorption conditions were refined via a univariate approach. This anion-exchange adsorbent exhibited high extraction recoveries (86.2-96.5 %) through synergistic hydrogen bonding, π-π stacking, hydrophobic, and anion-exchange/electrostatic interactions. The developed method demonstrated excellent analytical performance, with limits of detection ranging from 0.06 to 0.13 µgL⁻¹, linearity between 0.5-50 µgL⁻¹ (R² = 0.9992-0.9997), enrichment factors of 172-195, and intra-/inter-day RSDs below 7.7 %. Overall, the proposed method offers a rapid, simple, and sensitive approach that can be opted for the selective enrichment and determination of acidic/anionic contaminants including pharmaceuticals and pesticides in environmental waters and potentially other complex matrices such as drug formulations, food, and biological samples.
Accurate prediction of groundwater quality is essential for environmental monitoring and public health protection, particularly in arid regions such as Béchar in southwest Algeria. This study applied a root mean square-based water quality index (RMS-WQI) to evaluate groundwater quality using 621 samples characterized by physicochemical parameters, including pH, electrical conductivity, total dissolved solids, major cations, major anions, and nitrate. Seven supervised machine learning algorithms K-nearest neighbors, artificial neural network (ANN), support vector machine (SVM), ensemble trees (EN), discriminant analysis, Naïve Bayes, and decision trees were trained and optimized in MATLAB using the Classification Learner Toolbox with Bayesian optimization and fivefold cross-validation. Among the tested models, ANN and SVM achieved the highest predictive performance, with accuracies of 99.47 and 97.88%, respectively, along with superior precision, recall, F1-score, and Cohen's Kappa values, indicating strong agreement with observed RMS-WQI classes. Compared to conventional RMS-WQI assessment and previously reported nonoptimized models, the proposed framework demonstrates improved classification accuracy and robustness. Additionally, an operational graphical user interface was developed to facilitate rapid groundwater quality estimation using routine measurements. The findings highlight the effectiveness of optimized ANN and SVM models as reliable decision support tools for groundwater quality management in data-scarce arid environments.
Advanced primary treatment (APT) technologies are increasingly recognized as key components in the development of next-generation wastewater treatment plants (WWTPs), driven by their high pollutant removal efficiency, reduced energy demand, and contribution to climate-neutral operation. This review systematically evaluates the performance of major APT processes - including chemically enhanced primary treatment (CEPT), microsieving, flotation, electrocoagulation, integrated systems, and conventional sedimentation. Multiple visualization tools were applied to compare removal efficiencies and operational characteristics across technologies. The analysis demonstrates that all advanced techniques consistently outperform conventional gravity-driven sedimentation, highlighting the limitations of traditional primary treatment. Electrocoagulation and integrated systems achieve the highest overall removal efficiencies across multiple parameters, while CEPT, flotation, and microsieving exhibit strong performance in removing suspended solids, turbidity, and particulate-bound organic matter. However, these latter technologies show limited and highly variable nutrient removal, particularly for total nitrogen, reflecting both inherent process constraints and a lack of comprehensive studies.In addition, the review assesses economic and environmental aspects, revealing that microsieving and sedimentation offer lower costs and reduced carbon footprints, albeit with limited nutrient control. In contrast, electrocoagulation and integrated systems provide superior treatment performance at higher capital and operational costs, restricting their application to plants facing stringent effluent requirements.
The growth and reproductive performance of fish are influenced by ecological factors. This study investigated the biology of the climbing perch, Anabas testudineus, in relation to habitat. A total of 2,880 climbing perch were collected from three habitats (irrigation canal, swamp and paddy field) in Peninsular Malaysia during the dry and rainy seasons, and their biometric measurements (total length and body weight) and sexual maturity indices were measured. Two-way Classification Analysis (TCA) revealed significant sexual dimorphism in all morphometric parameters, significant habitat effects on fish size, and pronounced seasonal variation in environmental parameters, while condition factor and seasonal effects on morphometrics were not significant. Results showed that body size was largest in fish from irrigation canals during the rainy season, with males averaging 12.84 ± 1.17 cm in total length (32.38 ± 4.4 g body weight) and females averaging 13.70 ± 1.83 cm (52.84 ± 12.54 g), consistent with the upper size range reported for this species. Fish from irrigation canals also exhibited more advanced gonadal development, confirmed by higher gonadosomatic indices (GSI) and histological evidence of vitellogenic oocytes in females and spermatozoa-filled seminiferous lobules in males. Principal Component Analysis (PCA) indicated that larger body sizes and advanced gonadal development were associated with higher dissolved oxygen and pH, whereas smaller sizes correlated with elevated water temperature. This study highlights the critical roles of sex, habitat quality and seasonal variation in shaping the growth and reproductive traits of wild climbing perch populations and provides evidence-based insights for fisheries management in tropical freshwater ecosystems. Tumbesaran dan prestasi pembiakan ikan dipengaruhi oleh faktor-faktor ekologi. Kajian ini menyelidik beberapa aspek biologi ikan puyu, Anabas testudineus yang berkaitan dengan habitat mereka. Sejumlah 2,880 ikan puyu telah dikumpulkan dari tiga habitat (iaitu terusan pengairan, paya dan sawah padi) di Semenanjung Malaysia semasa musim panas dan hujan, dan parameter morfometrik serta indeks kematangan seksual mereka diukur dan dianggarkan. Keputusan menunjukkan perbezaan yang signifikan (P < 0.05) dalam kebanyakan parameter antara ikan jantan dan betina, serta merentasi habitat dan musim. Saiz badan ikan puyu yang disampel semasa musim hujan dari terusan pengairan adalah paling besar berbanding musim panas dan habitat lain (jantan, 12.84 ± 1.17 cm panjang keseluruhan dan 32.38 ± 4.4 g berat badan; betina, 13.70 ± 1.83 cm panjang keseluruhan dan 52.84 ± 12.54 g berat badan). Ikan dari terusan pengairan semasa musim hujan menunjukkan saiz badan terbesar dan perkembangan gonad yang lebih bagus, seperti yang dibuktikan oleh indeks gonadosomatik (GSI) yang lebih tinggi dan gamet yang terbeza dengan baik berbanding dengan ikan dari habitat lain. Trend kualiti air menunjukkan bahawa saiz badan yang lebih besar dikaitkan dengan tahap oksigen terlarut (DO) dan pH yang lebih tinggi, manakala saiz badan yang lebih kecil dikaitkan dengan suhu air yang tinggi. Kajian ini menekankan peranan penting kualiti habitat, variasi bermusim, dan jantina dalam membentuk ciri-ciri tumbesaran dan pembiakan populasi ikan puyu liar.
This study examines the temporal dynamics of petroleum hydrocarbon contamination and natural attenuation processes in riverine surface waters affected by military-related accidental pollution. Time-series monitoring data from six rivers located in eastern and western regions were analysed to quantify concentration exceedances, rates of decline, and differences in self-purification capacity among river systems. Petroleum hydrocarbon concentrations were determined using a standardised fluorimetric method, and their temporal behaviour was evaluated through descriptive statistics and first-order kinetic modelling. Extremely high peak concentrations were recorded following accidental releases, exceeding regulatory thresholds for fisheries and domestic water use by one to two orders of magnitude. Although a consistent decreasing trend was observed in all rivers, median and mean concentrations in several cases remained above regulatory limits for extended periods. Estimated half-times of concentration reduction varied markedly among rivers, reflecting differences in hydrological conditions, channel morphology, urbanisation, and dilution capacity. The results demonstrate that natural attenuation plays a significant role in reducing petroleum hydrocarbon levels, but is insufficient to fully offset the impacts of large-scale and repeated pollution events under conflict conditions. These findings highlight the need for integrated monitoring, targeted mitigation measures, and long-term restoration strategies to support sustainable water management during post-conflict recovery.
Efficient monitoring of triazine herbicide residues is essential for safeguarding environmental and food safety. In this work, an innovative imidazolium-functionalized ionic conjugated microporous polymer (Im-CMP) was developed through Sonogashira-Hagihara coupling polymerization, and for the first time utilized as an adsorbent for solid-phase extraction (SPE) to enrich seven triazine herbicides from environmental water and fruit juice samples. Comprehensive characterizations confirmed that Im-CMP possessed a stable porous structure, high thermal stability, abundant π-π conjugated framework, and excellent hydrophilicity (water contact angle: 25.1°) derived from imidazolium ionic moieties, which solved the defect of poor aqueous dispersibility of traditional neutral CMPs. Density functional theory calculations and independent gradient model analysis revealed that the high extraction capacity of Im-CMP for triazine herbicides was dominated by efficient π-π stacking interactions, with synergistic contributions from directional weak interactions including C-H···π and N-H···π. Under optimized conditions, the established Im-CMP-SPE-HPLC-MS/MS method exhibited a wide linear range (0.25-250 ng·L⁻¹), low detection limits (0.03-0.11 ng·L⁻¹), high enrichment factors (387-554), and satisfactory recoveries (77.4-110.7%) with good precision. Additionally, the Im-CMP adsorbent demonstrated excellent reusability for nine cycles and consistent batch-to-batch reproducibility. This work not only provides a rational design strategy for ionic-functionalized porous adsorbents for sample pretreatment, but also establishes a sensitive, reliable and practical analytical method for the trace monitoring of triazine herbicides in complex environmental and food matrices, and further expands the application of ionic conjugated microporous polymers in the field of pesticide residue analysis.
This study investigated the coagulation effect of magnetized polyferric sulfate (PFS) and polyacrylamide (PAM) on papermaking wastewater. Results showed that the co-magnetized PFS-PAM group (Group C) achieved significantly higher removal rates of chemical oxygen demand (COD), color, turbidity, and UV254 than the nonmagnetized PFS-PAM group (Group B) and control group (Group A). Specifically, the effluent COD of Group C decreased to 46.72 mg/L, with color, turbidity, and UV254 removal rates increased by 16.85, 32.38, and 10.78%, respectively, compared with Group A. The enhanced efficiency was attributed to the cutting effect of magnetic induction lines in alternating magnetic fields (AMFs), which promoted coagulation and sedimentation. AMFs converted magnetic energy into internal energy of PFS particles, increasing multinuclear polymers in PFS solutions and strengthening complexation and chelation reactions. Orthogonal experiments identified the optimal parameter combination as A3B1C1D3E3 (PFS dosage: 1,000 mg/L, PAM dosage: 1.5 mg/L, magnetization intensity: 6 mT, magnetization time: 5 min, magnetization frequency: 130 Hz), under which the removal rates of COD, color, turbidity, and UV254 reached 94.2, 93.08, 90.07, and 89.35%, respectively. Importantly, PAM did not alter the magnetization effect, supporting the wide application of AMFs in wastewater treatment.
Swine wastewater contains recoverable energy, but anaerobic digestion is often limited by complex organics and slow hydrolysis. To overcome this limitation, this study introduced nanobubble technology using three gas media (air, O2, and O3) and systematically studied their effects on methane recovery during the anaerobic digestion of swine wastewater. Batch experiments showed that O3 nanobubbles achieved the strongest enhancement, increasing cumulative methane production by 87.5% compared with the control. This improvement may result from the strong oxidative capacity of O3 nanobubbles to degrade recalcitrant organics, as indicated by the second methane production peak observed only in the O3 nanobubbles. In contrast, O2 nanobubbles provided the weakest improvement, potentially because excess dissolved oxygen stimulated facultative aerobic respiration, converting substrates to CO2 and lowering availability for methanogenesis. Further analysis revealed that all nanobubble treatments accelerated volatile fatty acid turnover and enriched key hydrolytic and acidogenic microbes, particularly under O3 nanobubbles. The enrichment of Methanothrix and downregulation of the energy-intensive PilA gene suggest promoted electron transfer. Negatively charged nanobubbles may act as abiotic mediators that facilitate direct interspecies electron transfer. Metabolic analysis indicated enhanced hydrogenotrophic, methylotrophic, and acetoclastic methanogenesis, implying strengthened synergy among pathways. Overall, O3 nanobubbles show promise for resource recovery from organic waste.
Arboviruses, such as yellow fever and dengue viruses, pose a growing public health threat in Sub-Saharan Africa, particularly at human-wildlife interfaces. Mole National Park (MNP), with its rich biodiversity and ecotourism, represents a high-risk area and has been the epicentre of recent outbreaks in Ghana. The objective of this study was to assess community knowledge, attitudes and practices (KAP) regarding arboviral transmission and prevention in this high-risk interface. In December 2023, we conducted a cross-sectional KAP survey among 300 adults in MNP (n = 120) and nearby communities, Murugu (n = 94) and Mognori (n = 86) using structured questionnaires. Data were analysed using descriptive statistics and chi-square tests, and a multivariable logistic regression model (α = .05). Awareness of yellow fever was high (92.0%), but none mentioned dengue or Zika; awareness varied significantly by location (MNP 96.7%, Murugu 96.8%, Mognori 80.2%; P < .001). Only 44.0% correctly associated mosquito bites with yellow fever transmission. Fever was cited as a common symptom by 17.0%, but misconceptions such as "yellow vomit" (5.0%) and "yellow urine" (10.3%) persisted. While nearly all (95.7%) reported using Insecticide-treated nets, adoption of other preventive measures like repellents (5.0%) and environmental management (1.0%) was very low. Perceptions of arbovirus presence also differed significantly across communities (MNP 48.4%, Murugu 38.7%, Mognori 12.9%; P < .001). Despite these knowledge gaps, all respondents indicated they would seek medical care if infected. These findings suggest that, despite high awareness of yellow fever, knowledge gaps persist regarding its symptoms, transmission, and preventive measures. Addressing these requires sustained health education initiatives on arboviral disease transmission, improved access to repellents and water, sanitation, and hygiene tools, and a One Health approach that integrates human, animal, and environmental health.
Xylanases are widely used in baking, seafood processing, and paper production, but their performance is often compromised under high-salt, acidic, or alkaline conditions, limiting broader industrial deployment. Identifying robust xylanases from saline-alkali environments is therefore of practical importance. Here, we report a GH10 xylanase gene, XynE102, mined from a saline-alkali soil metagenome from Karamay, Xinjiang. The deduced amino acid sequence shares 69.17% identity with a xylanase from Cellvibrionaceae bacterium (GenBank accession HEY7885703.1). XynE102 was cloned and heterologously expressed in Escherichia coli, and the recombinant enzyme was purified by Ni-NTA affinity chromatography. Using beechwood xylan as substrate, XynE102 exhibited optimal activity at 50 °C and pH 7.0. It retained ≥ 50% relative activity between 30 and 55 °C and pH 5.6-8.6, and ≥ 75% activity in 2.0 M NaCl. Notably, after preincubation at 40 °C for 60 and 120 min, its activity increased to 130% and 165% of the initial value, respectively. Following 24 h preincubation at pH 7-10, residual activity remained ≥ 80%, indicating pronounced alkaline stability. At 1 mM, Mn2+, Co2+, and Fe3+ activated the enzyme, whereas Mg2+, Cu2+, and Cd2+ inhibited it; 1% SDS had no measurable effect. XynE102 primarily hydrolyzed xylan to xylobiose and xylotetraose. It also hydrolyzed alkali-treated corn stalk and hot-water-pretreated wheat bran, yielding reducing sugar concentrations of 5.44 mM and 4.18 mM, respectively, after 24 h. Taken together, these results indicate that XynE102 is a neutral-pH xylanase with notable salt and alkali tolerance, supporting its potential for prebiotic XOS production and food-processing applications under moderate temperature conditions.
Plastispheres, microbial biofilms formed on plastic surfaces, are increasingly recognised as ecological niches capable of transporting pollutants and antibiotic-resistant microorganisms. However, mechanistic insights into antimicrobial resistance (AMR) dynamics in natural plastispheres remain limited, particularly for priority pathogens such as carbapenem-resistant Enterobacterales (CRE). Here, we evaluated plastispheres as environmental reservoirs and vectors of carbapenem-resistant bacteria, comparing wastewater (secondary settling tanks, representing the final stage before environmental discharge) and riverine environments. Using a combined SEM-CFM approach, we resolved plastic surface topography and the spatial organisation of biofilm-associated bacteria. Although CRE were not detected, carbapenem-resistant bacteria constituted a stable fraction of heterotrophic communities in both environments and were primarily associated with intrinsic resistance mechanisms. Carbapenem-resistant isolates included Aeromonas spp. (blaCphA), Stenotrophomonas maltophilia (blaL1), and Pseudomonas putida (efflux-based resistance). Microscopy revealed dense bacterial clusters on plastic surfaces, suggesting microenvironments that may facilitate cell-cell interactions, including horizontal gene transfer. These findings highlight plastispheres not only as vectors of AMR but also as potential evolutionary hotspots shaping resistance persistence and dissemination in aquatic systems. Future integrating metagenomic and genomic data on resistance gene mobility with spatially resolved microbial community structure will provide critical insights into the mechanisms and risks of AMR dissemination in plastisphere environments.
Polysaccharides derived from sea buckthorn pomace are bioactive compounds that can undergo intestinal fermentation and exert prebiotic effects. However, the influence of sequential extraction on their structural properties and prebiotic activity remains unexplored. Six fractions were sequentially extracted with water (W), CDTA (CA), sodium carbonate (SC), and 0.1, 1, and 4 mol/L NaOH (SH0.1, SH1, SH4), and their fermentation characteristics were compared by using an in vitro fecal fermentation model. SH1 and SH4 were enriched in glucose and xylose, whereas CA and SC contained more galactose, arabinose, and rhamnose, indicating they were pectic contributions. CA and SC markedly increased acetate and propionate production, while SH0.1, SH1, and SH4 favored propionate accumulation. All fractions enriched Parabacteroides; Bacteroides was more abundant in the CA and SH1 groups, and Bifidobacterium was most abundant in the W group. These findings indicate that compositional differences among polysaccharide fractions influence gut microbial composition and SCFA production.
Escherichia coli (E. coli) is a microorganism commonly found in water and food matrices, and its rapid and accurate detection is crucial for maintaining public health and ensuring food safety. However, traditional molecularly imprinted polymer (MIP) sensors often face challenges such as tedious template removal and prolonged sensing times. This study develops a label-free bacterial molecularly imprinted sensor that utilizes the synergistic effect of polypyrrole (PPy) and multi-walled carbon nanotubes (MWCNTs) to achieve highly sensitive detection of E. coli. Based on the large specific surface area and superior conductivity of MWCNTs, as well as the favorable electrochemical polymerization properties of PPy, a PPy/MWCNTs composite film was fabricated via a one-step electropolymerization process. The prepared sensor exhibited excellent kinetic characteristics, with a template removal time of only 15 min, and could be regenerated and used for subsequent detection within 30 min. Under optimized conditions, the biosensor showed a satisfactory linear response over the concentration range of 102-108 CFU/mL, with a low detection limit of 65 CFU/mL (3σ/S). Furthermore, recovery experiments conducted in tap water and lemon juice samples yielded satisfactory recoveries ranging from 87.1% to 114.8%, demonstrating the reliability and practical applicability of the proposed sensor for bacterial detection in real samples. This sensor offers advantages such as simple preparation, low material cost, and high sensitivity, providing a reliable and practical analytical platform for the rapid and reliable detection of bacteria.
The demand for sustainable methods to extract bioactive compounds from fruits is increasing, yet conventional extraction methods are limited by their reliance on large amounts of organic solvents, limiting their widespread application. Therefore, we evaluated a deep eutectic solvent (DES)-ultrasound-assisted extraction to efficiently extract phenolic compounds from Lonicera caerulea L. berries. Using single-factor experiments and response surface methodology, the optimal conditions were determined: A DES composed of choline chloride and 1,3-butanediol at a 1:5 molar ratio, with 29% water content, a solid-liquid ratio of 1:41 g/mL, and ultrasonication for 50 min. This method yielded 68.63 ± 0.46 mg gallic acid/g of total polyphenols, a 1.5-fold increase over the conventional solvent (50% ethanol). Furthermore, UHPLC-Q-TOF-MS/MS analysis confirmed the presence of 31 phytochemicals in the extract, including cyanidin-3-O-glucoside, cyanidin-3-O-rutinoside, chlorogenic acid, procyanidin B2, rutin, and quercitrin, among others. Scanning electron microscopy analysis confirmed the synergistic mechanism of DES permeation and ultrasound-induced cell wall disruption, and the mechanism of DES formation was studied by Fourier transform infrared spectroscopy. Further studies revealed that the extract exhibited significant antioxidant activity, with IC50 values of 8.57 ± 0.19 µg/mL, 409.13 ± 6.77 µg/mL, and 123.17 ± 3.25 µg/mL for DPPH•, •OH, and ABTS+• assays, respectively, and demonstrated pancreatic lipase inhibition with an IC50 of 4.31 ± 0.12 mg/mL. In the zebrafish model of non-alcoholic fatty liver disease, the extract (200 µg/mL) significantly reduced hepatic lipid accumulation, and decreased total cholesterol, triglycerides, alanine aminotransferase, and aspartate aminotransferase levels by 64%, 60%, 60%, and 55%, respectively, confirming potent lipid-lowering and hepatoprotective efficacy. Overall, DES combined with ultrasound-assisted extraction could serve as an eco-friendly method for recovering high-value compounds from fruits and their byproducts.