Eutrophication-induced shifts cause diverse responses in the phoD community of a plateau freshwater lake.

Eutrophication is a critical environmental challenge affecting lakes globally. Mitigating trophic level under endogenous phosphorus release is an unsolved problem in eutrophic lakes. However, understanding the dynamics and assembly of microbial communities encoding the alkaline phosphatase (phoD community) and their responses during trophic transitions in eutrophic lakes is limited. In this study, we compared the composition and assembly mechanisms of phoD communities in four seasons in the Yilong Lake, a shallow lake of the Yunnan-Guizhou Plateau. The lake exhibits slightly eutrophic conditions in summer and mesotrophic conditions in spring, autumn, and winter. By analyzing seasonal variations, we observed that during summer, the relative abundance of Pseudomonas in the water had the highest value, while the Shannon-Wiener index of phoD communities was lowest. Mantel tests showed an increased Bray-Curtis dissimilarity of phoD communities in the water with rising eutrophication, a trend not observed in sediment. Notably, eutrophication heightened the homogeneity selection governing the assembly of phoD communities in water. The co-occurrence networks showed that the OTUs in the summer exhibited closer interconnections than those in other seasons. Additionally, the topological parameters from networks indicated that eutrophication is poised to instigate changes and modulate the dynamics of the microbial phoD community, resulting in markedly distinct seasonal behaviors. pH was identified as a critical factor directly influencing phoD community diversity via partial least squares path modeling (PLS-PM). This study shed light on our understanding of the seasonal dynamics of phoD communities and their pivotal role in phosphorus cycling in eutrophic lakes.

Quality and Accountability of ChatGPT in Health Care in Low- and Middle-Income Countries: Simulated Patient Study.

Using simulated patients to mimic 9 established noncommunicable and infectious diseases, we assessed ChatGPT's performance in treatment recommendations for common diseases in low- and middle-income countries. ChatGPT had a high level of accuracy in both correct diagnoses (20/27, 74%) and medication prescriptions (22/27, 82%) but a concerning level of unnecessary or harmful medications (23/27, 85%) even with correct diagnoses. ChatGPT performed better in managing noncommunicable diseases than infectious ones. These results highlight the need for cautious AI integration in health care systems to ensure quality and safety.

Positive soil priming effects are the rule at a global scale.

Priming effects of soil organic matter decomposition are critical to determine carbon budget and turnover in soil. Yet, the overall direction and intensity of soil priming remains under debate. A second-order meta-analysis was performed with 9296-paired observations from 363 primary studies to determine the intensity and general direction of priming effects depending on the compound type, nutrient availability, and ecosystem type. We found that fresh carbon inputs induced positive priming effects (+37%) in 97% of paired observations. Labile compounds induced larger priming effects (+73%) than complex organic compounds (+33%). Nutrients (e.g., N, P) added with organic compounds reduced the intensity of priming effects compared to compounds without N and P, reflecting "nutrient mining from soil organic matter" as one of the main mechanisms of priming effects. Notably, tundra, lakebeds, wetlands, and volcanic soils showed much larger priming effects (+125%) compared to soils under forests, croplands, and grasslands (+24…+32%). Our findings highlight that positive priming effects are predominant in most soils at a global scale. Optimizing strategies to incorporate fresh organic matter and nutrients is urgently needed to offset the priming-induced accelerated organic carbon turnover and possible losses.

The power of green: Harnessing phytoremediation to combat micro/nanoplastics.

Plastic pollution and its potential risks have been raising public concerns as a global environmental issue. Global plastic waste may double by 2030, posing a significant challenge to the remediation of environmental plastics. In addition to finding alternative products and managing plastic emission sources, effective removal technologies are crucial to mitigate the negative impact of plastic pollution. However, current remediation strategies, including physical, chemical, and biological measures, are unable to compete with the surging amounts of plastics entering the environment. This perspective lays out recent advances to propel both research and action. In this process, phytoaccumulation, phytostabilization, and phytofiltration can be applied to reduce the concentration of nanoplastics and submicron plastics in terrestrial, aquatic, and atmospheric environments, as well as to prevent the transport of microplastics from sources to sinks. Meanwhile, advocating for a more promising future still requires significant efforts in screening hyperaccumulators, coupling multiple measures, and recycling stabilized plastics from plants. Phytoremediation can be an excellent strategy to alleviate global micro/nanoplastic pollution because of the cost-effectiveness and environmental sustainability of green technologies.

First-of-Its-Kind: Nationwide meta-analysis of microplastic pollution and risk assessment in Thailand.

Thailand ranks as the sixth largest contributor to global microplastic pollution, which is exacerbated by extensive plastic use. Despite rising concerns, no comprehensive review is available on microplastic contamination and its potential risk in Thailand. This review synthesised data on microplastic abundance and characteristics within the country from 118 peer-reviewed publications (2017-2024). We found predominant microplastic presence in crustaceans (1.69-160.15 items/g), followed by Mollusca (0.03-9.5 items/g) and fishes (0.01-28.17 items/g), with higher abundances in wastewater (4 × 102 to 6.09 × 105 items/m3) compared to that in freshwater (1.44-2.92 × 106 items/m3) and seawater (2.70 × 10-1 to 6.25 × 104 items/m3). Marine sediments (48.3-2.13 × 104 items/kg) also showed significantly higher microplastic concentrations than terrestrial sediments (3-2.92 × 103 items/kg). Predominant microplastics were identified as fibers (59.36% and 35.05% for biological and environmental samples, respectively) and fragments (24.14%, 30.68%) in blue (25.95%, 18.64%), and colourless/transparent (20.01%, 14.47%), primarily composed of polyethylene terephthalate (19.46%, 9.19%), nylon (3.23%, 9.99%), polypropylene (19.78%, 24.23%), and polyethylene (14.81%, 11.66%). The potential ecological risk was low in all ecosystems except for wastewater. Shrimp and fish were more susceptible to microplastics compared to other studies in the region. Additionally, the sources, transport, and pathways of microplastic pollution in Thailand's aquatic territories and the current measures and policies implemented by the government to address plastic pollution are discussed. This review has compiled up-to-date insights into the prevalence, distribution, and risks associated with microplastics, which is instrumental in formulating effective strategies for contaminant control and ultimately reducing plastic pollution.

Species pool and local assembly processes drive ß diversity of ammonia-oxidizing and denitrifying microbial communities in rivers along a latitudinal gradient.

Both regional species pool and local community assembly mechanism drive the microbial diversity patterns across geographical gradients. However, little has been done to separate their effects on the ß diversity patterns of microbial communities involved in nitrogen (N) cycling in river ecosystems. Here, we use high-throughput sequencing of the archaeal amoA, bacterial amoA, nirK, and nirS genes, null model, and neutral community model to distinguish the relative importance of species pool and local assembly processes for ammonia-oxidizing and denitrifying communities in river wetlands along a latitudinal gradient in eastern China. Results indicated that the ß diversity of the nirS-type denitrifying community co-varied with γ diversity and environmental heterogeneity, implying that regional species pool and heterogeneous selection explained variation in ß diversity. However, the ß diversity of ammonia-oxidizing and nirK-type denitrifying communities did not correlate with γ diversity and environmental heterogeneity. The continuous hump distribution of ß deviation along the latitudinal gradient and the lower species dispersal rate indicated that the dispersal limitation shaped the variation in ß diversity of ammonia-oxidizing and nirK-type denitrifying communities. Additionally, biotic interactions drove ammonia-oxidizing and nirS-type denitrifying communities by influencing species co-occurrence patterns. Our study highlights the importance of regional species pool and local community assembly processes in shaping geographical patterns of N-cycling microorganisms and extends knowledge of their adaptability to a continuously changing environment on a large scale.

Metagenomic insights into nitrogen-cycling microbial communities and their relationships with nitrogen removal potential in the Yangtze River.

Nitrogen (N) pollution is a major threat to river ecosystems worldwide. Elucidating the community structure of N-cycling microorganisms in rivers is essential to understanding how ecosystem processes and functions will respond to increasing N inputs. However, previous studies generally focus on limited functional genes through amplicon sequencing or quantitative PCR techniques and cannot cover all N-cycling microorganisms. Here, metagenomic sequencing and genome binning were used to determine N-cycling genes in water, channel sediments, and riparian soils of the Yangtze River, which has been heavily polluted by N. Additionally, the denitrification and anaerobic ammonium oxidation (anammox) rates that reflect N removal potential were measured using 15N isotope pairing technique. Results showed that functional genes involved in organic N metabolism (i.e., organic degradation and synthesis) and nitrate reduction pathways (i.e., dissimilatory and assimilatory nitrate reduction to ammonium and denitrification) were more abundant and diverse than other N-cycling genes. A total of 121 metagenome-assembled genomes (MAGs) were identified to be involved in N-cycling processes, and the key MAGs were mainly taxonomically classified as Alphaproteobacteria and Gammaproteobacteria. The abundance and diversity of most N-cycling genes were higher in soils and sediments than in water, as well as higher in downstream and midstream than in upstream sites. These spatial variations were explained not only by local environment and vegetation but also by geographical and climatic factors. N removal process (i.e., denitrification and anammox) rates were significantly related to the abundance or diversity of several N-cycling genes, and climate and edaphic factors could regulate denitrification and anammox rates directly and indirectly through their effects on functional genes. Overall, these results provide a new avenue for further understanding the biogeographic patterns and environmental drivers of N-cycling microorganisms in rivers from the metagenomic perspective.

Nonbiodegradable microplastic types determine the diversity and structure of soil microbial communities: A meta-analysis.

As an emerging contaminant, microplastics (MPs) have received considerable attention for their potential threat to the soil environment. However, the response of soil bacterial and fungal communities to MPs exposure remains unclear. In this study, we conducted a global meta-analysis of 95 publications and 2317 observations to assess the effects of nonbiodegradable MP properties and exposure conditions on soil microbial biomass, alpha and beta diversity, and community structure. Our results indicate that MPs increased (p < 0.05) soil active microbial biomass by 42%, with the effect varying with MPs type, exposure concentration, exposure time and soil pH. MPs concentration was identified as the most important factor controlling the response of soil microbial biomass to MPs. MPs addition decreased (p < 0.05) the soil bacterial Shannon and Chao1 indices by 2% and 3%, respectively, but had limited effects (p > 0.05) on soil fungal Shannon and Chao1 indices. The type of MPs and exposure time determined the effects of MPs on bacterial Shannon and Chao1 indices, while the type of MPs and soil pH controlled the response ratios of fungal Shannon and Chao1 indices to MPs. Specifically, soil organic carbon (SOC) was the major factor regulating the response ratio of bacterial alpha diversity index to MPs. The presence of MPs did not affect soil bacterial community structure and beta diversity. Our results highlight that MPs reduced bacterial diversity and richness but increased the soil active microbial biomass, suggesting that MPs could disrupt biogeochemical cycles by promoting the growth of specific microorganisms.

Photodegradation of bisphenol A (BPA) in coastal aquaculture waters: Influencing factors, products, and pathways.

Bisphenol A (BPA), an endocrine-disrupting contaminant, is ubiquitous in the environment due to its presence in plastics, wastewater, and agricultural runoff. This study investigated the photodegradation behavior of BPA in coastal aquaculture waters near Qingdao, China. Lower salinity promoted BPA photodegradation, while higher salinity has an inhibitory effect, suggesting slower degradation in seawater compared to ultrapure water. Triplet-excited dissolved organic matter (3DOM*) was identified as the primary mediator of BPA degradation, with additional contributions from hydroxyl radicals (•OH), singlet oxygen (1O2), and halogen radicals (HRS). Alepocephalidae aquaculture water exhibited the fastest degradation rate, likely due to its high DOM and nitrate/nitrite (NO3-/NO2-) content, which are sources of 3DOM* and •OH. A positive correlation existed between NO3-/NO2- concentration and the BPA degradation rate. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) analysis identified the primary BPA photodegradation products, formed mainly through oxidative degradation, hydroxyl substitution, nitration, and chlorination pathways. Elucidating these photodegradation mechanisms provides valuable insights into the environmental fate and potential ecological risks of BPA in aquaculture environments. This knowledge can inform strategies for marine environmental protection and the development of sustainable practices.

Distinct species turnover patterns shaped the richness of antibiotic resistance genes on eight different microplastic polymers.

Elucidating the formation mechanism of plastisphere antibiotic resistance genes (ARGs) on different polymers is necessary to understand the ecological risks of plastisphere ARGs. Here, we explored the turnover and assembly mechanism of plastisphere ARGs on 8 different microplastic polymers (4 biodegradable (bMPs) and 4 non-biodegradable microplastics (nMPs)) by metagenomic sequencing. Our study revealed the presence of 479 ARGs with abundance ranging from 41.37 to 58.17 copies/16S rRNA gene in all plastispheres. These ARGs were predominantly multidrug resistance genes. The richness of plastisphere ARGs on different polymers had a significant correlation with the contribution of species turnover to plastisphere ARGs ß diversity. Furthermore, polymer type was the most critical factor affecting the composition of plastisphere ARGs. More opportunistic pathogens carrying diverse ARGs on BMPs (PBAT, PBS, and PHA) with higher horizontal gene transfer potential may further magnify the ecological risks and human health threats. For example, the opportunistic pathogens Riemerella anatipestifer, Vibrio campbellii, and Vibrio cholerae are closely related to human production and life, which were the important potential hosts of many plastisphere ARGs and mobile genetic elements on BMPs. Thus, we emphasize the urgency of developing the formation mechanism of plastisphere ARGs and the necessity of controlling BMPs and ARG pollution, especially BMPs, with ever-increasing usage in daily life.

Internal transformation and damming regulate the longitudinal variation of DOM bioavailability in a large river.

Understanding the spatial patterns of dissolved organic matter (DOM) and factors that influence them is crucial for maintaining river ecosystem functions and riverine health, considering the significant role of DOM in water quality and aquatic ecosystems. Nevertheless, there is limited knowledge regarding the spatial variation of DOM bioavailability and the factors driving them in large river systems. This study involved 39 sampling locations along the main stem of the Changjiang River, spanning its entire length (>5000 km) during a dry season. Spatial patterns of DOM were assessed by measurements of DOC concentrations and eight fluorescence DOM indices, namely fluorescence index (FI-A and FI-B), Trytophan/Tyrosine, Humic A, Humic C, humification indices (HIX-A and HIX-B), and Freshness index (ß/α). The results revealed that the water DOM in the main stem of the Changjiang River primarily originated from terrestrial sources. A decline in DOM bioavailability was observed from the upper to the lower basin, aligning with the carbon processing prediction rather than the river continuum concept (RCC). The pure effect of physicochemical factors (25.30%) was greater than that of geographic factors (9.40%). The internal transformation processes determined the significant longitudinal decreases of DOM bioavailability. While no significant difference in DOM bioavailability was observed between reaches before and after the dams, the construction of dams was found to improve DOM bioavailability at the subsection scale and reduce the spatial autocorrelation of DOM bioavailability across the entire basin.

Lipocalin-2-mediated intestinal epithelial cells pyroptosis via NF-κB/NLRP3/GSDMD signaling axis adversely affects inflammation in colitis.

Ulcerative colitis (UC) is a major inflammatory bowel disease (IBD) characterized by intestinal epithelium damage. Recently, Lipocalin-2 (LCN2) has been identified as a potential fecal biomarker for patients with UC. However, further investigation is required to explore its pro-inflammatory role in UC and the underlying mechanism. The biological analysis revealed that Lcn2 serves as a putative signature gene in the colon mucosa of patients with UC and its association with the capsase/pyroptosis signaling pathway in UC. In wild-type mice with DSS-induced colitis, LCN2 overexpression in colon mucosa via in vivo administration of Lcn2 overexpression plasmid resulted in exacerbation of colitis symptoms and epithelium damage, as well as increased expression levels of pyroptosis markers (cleaved caspase1, GSDMD, IL-1ß, HMGB1 and IL-18). Additionally, we observed downregulation in the expression levels of pyroptosis markers following in vivo silencing of LCN2. However, the pro-inflammatory effect of LCN2 overexpression was effectively restrained in GSDMD-KO mice. Moreover, single-cell RNA-sequencing analysis revealed that Lcn2 was predominantly expressed in the intestinal epithelial cells (IECs) within the colon mucosa of patients with UC. We found that LCN2 effectively regulated pyroptosis events by modulating the NF-κB/NLRP3/GSDMD signaling axis in NCM460 cells stimulated by LPS and ATP. These findings demonstrate the pro-inflammatory role of LCN2 in colon epithelium and provide a potential target for inhibiting pyroptosis in UC.

Convergence effect during spatiotemporal succession of lacustrine plastisphere: loss of priority effects and turnover of microbial species.

Succession is a fundamental aspect of ecological theory, but studies on temporal succession trajectories and ecological driving mechanisms of plastisphere microbial communities across diverse colonization environments remain scarce and poorly understood. To fill this knowledge gap, we assessed the primary colonizers, succession trajectories, assembly, and turnover mechanisms of plastisphere prokaryotes and eukaryotes from four freshwater lakes. Our results show that differences in microbial composition similarity, temporal turnover rate, and assembly processes in the plastisphere do not exclusively occur at the kingdom level (prokaryotes and eukaryotes), but also depend on environmental conditions and colonization time. Thereby, the time of plastisphere colonization has a stronger impact on community composition and assembly of prokaryotes than eukaryotes, whereas for environmental conditions, the opposite pattern holds true. Across all lakes, deterministic processes shaped the assembly of the prokaryotes, but stochastic processes influenced that of the eukaryotes. Yet, they share similar assembly processes throughout the temporal succession: species turnover over time causes the loss of any priority effect, which leads to a convergent succession of plastisphere microbial communities. The increase and loss of microbial diversity in different kingdoms during succession in the plastisphere potentially impact the stability of entire microbial communities and related biogeochemical cycles. Therefore, research needs to integrate temporal dynamics along with spatial turnovers of the plastisphere microbiome. Taking the heterogeneity of global lakes and the diversity of global climate patterns into account, we highlight the urgency to investigate the spatiotemporal succession mechanism of plastisphere prokaryotes and eukaryotes in more lakes around the world.

A metagenome-derived artificial intelligence modeling framework advances the predictive diagnosis and interpretation of petroleum-polluted groundwater.

Groundwater (GW) quality monitoring is vital for sustainable water resource management. The present study introduced a metagenome-derived machine learning (ML) model aimed at enhancing the predictive understanding and diagnostic interpretation of GW pollution associated with petroleum. In this framework, taxonomic and metabolic profiles derived from GW metagenomes were combined for use as the input dataset. By employing strategies that optimized data integration, model selection, and parameter tuning, we achieved a significant increase in diagnostic accuracy for petroleum-polluted GW. Explanatory artificial intelligence techniques identified petroleum degradation pathways and Rhodocyclaceae as strong predictors of a pollution diagnosis. Metagenomic analysis corroborated the presence of gene operons encoding aminobenzoate and xylene biodegradation within the de novo assembled genome of Rhodocyclaceae. Our genome-centric metagenomic analysis thus clarified the ecological interactions associated with microbiomes in breaking down petroleum contaminants, validating the ML-based diagnostic results. This metagenome-derived ML framework not only enhances the predictive diagnosis of petroleum pollution but also offers interpretable insights into the interaction between microbiomes and petroleum. The proposed ML framework demonstrates great promise for use as a science-based strategy for the on-site monitoring and remediation of GW pollution.

Build Deep Neural Network Models to Detect Common Edible Nuts from Photos and Estimate Nutrient Portfolio.

Nuts are nutrient-dense foods and can be incorporated into a healthy diet. Artificial intelligence-powered diet-tracking apps may promote nut consumption by providing real-time, accurate nutrition information but depend on data and model availability. Our team developed a dataset comprising 1380 photographs, each in RGB color format and with a resolution of 4032 × 3024 pixels. These images feature 11 types of nuts that are commonly consumed. Each photo includes three nut types; each type consists of 2-4 nuts, so 6-9 nuts are in each image. Rectangular bounding boxes were drawn using a visual geometry group (VGG) image annotator to facilitate the identification of each nut, delineating their locations within the images. This approach renders the dataset an excellent resource for training models capable of multi-label classification and object detection, as it was meticulously divided into training, validation, and test subsets. Utilizing transfer learning in Python with the IceVision framework, deep neural network models were adeptly trained to recognize and pinpoint the nuts depicted in the photographs. The ultimate model exhibited a mean average precision of 0.7596 in identifying various nut types within the validation subset and demonstrated a 97.9% accuracy rate in determining the number and kinds of nuts present in the test subset. By integrating specific nutritional data for each type of nut, the model can precisely (with error margins ranging from 0.8 to 2.6%) calculate the combined nutritional content-encompassing total energy, proteins, carbohydrates, fats (total and saturated), fiber, vitamin E, and essential minerals like magnesium, phosphorus, copper, manganese, and selenium-of the nuts shown in a photograph. Both the dataset and the model have been made publicly available to foster data exchange and the spread of knowledge. Our research underscores the potential of leveraging photographs for automated nut calorie and nutritional content estimation, paving the way for the creation of dietary tracking applications that offer real-time, precise nutritional insights to encourage nut consumption.

Diversity and biogeography of bacterial community in the Ili River network varies locally and regionally.

Microorganisms in rivers indeed play a crucial role in nutrient cycling within aquatic ecosystems. Understanding the assembly mechanisms of bacterial communities in river networks is essential for predicting their special composition and functional characteristics in natural rivers. This study employed 16S rRNA gene amplicon sequence variation (ASVs) to scrutinize the bacterial community within the uniquely topographical Ili River network. The bacterial community composition varied across the three tributaries with distinct sources and the mainstream. The confluence of various sources diminished the diversity of the bacterial community and altered the functionality of within mainstream. We suggest that strong dispersal limitation predominantly shaped the community at the regional scale (46.6 %), underscoring the significant contribution of headwater sites to bacterial community composition. Contrary to expectation, the bacterial resources in the mainstream were not enriched by the higher diversity in three tributaries. Instead, confluence disturbance potentially increased the undominated processes (36.7 %) and alter the bacterial community composition at the local scale of the mainstream. The intricate coalescence at the confluence could potentially be an intriguing causative factor. Our research indicates that the composition of bacterial communities within intricate river networks exhibits biogeographic patterns, simultaneously influenced by river confluence and geographical features, necessitating multi-scale analysis.

Selected legacy and emerging organic contaminants in sediments of China's Yangtze - the world's third longest river: Response to anthropogenic activities.

To explore contaminant concerns as a result of anthropogenic disturbance of the river system, this study provided the first extensive investigation of the contamination profiles, possible driving factors, and ecological risks of 40 target compounds including pharmaceuticals and personal care products (PPCPs), neonicotinoid pesticides (NNIs), polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs) in sediments of the whole Yangtze River (the world's third longest river). Among these target compounds, PPCPs were the dominant contaminants with a total concentration (∑15PPCPs) of 2.13-14.99 ng/g, followed by ∑7PCBs (

Health risk ranking of antibiotic resistance genes in the Yangtze River.

Antibiotic resistance is an escalating global health concern, exacerbated by the pervasive presence of antibiotic resistance genes (ARGs) in natural environments. The Yangtze River, the world's third-longest river, traversing areas with intense human activities, presents a unique ecosystem for studying the impact of these genes on human health. Here, we explored ARGs in the Yangtze River, examining 204 samples from six distinct habitats of approximately 6000 km of the river, including free-living and particle-associated settings, surface and bottom sediments, and surface and bottom bank soils. Employing shotgun sequencing, we generated an average of 13.69 Gb reads per sample. Our findings revealed a significantly higher abundance and diversity of ARGs in water-borne bacteria compared to other habitats. A notable pattern of resistome coalescence was observed within similar habitat types. In addition, we developed a framework for ranking the risk of ARG and a corresponding method for calculating the risk index. Applying them, we identified water-borne bacteria as the highest contributors to health risks, and noted an increase in ARG risks in particle-associated bacteria correlating with heightened anthropogenic activities. Further analysis using a weighted ARG risk index pinpointed the Chengdu-Chongqing and Yangtze River Delta urban agglomerations as regions of elevated health risk. These insights provide a critical new perspective on ARG health risk assessment, highlighting the urgent need for strategies to mitigate the impact of ARGs on human health and to preserve the ecological and economic sustainability of the Yangtze River for future human use.

Can "Risk-Sharing" Mechanisms Help Clonal Aquatic Plants Mitigate the Stress of Nanoplastics?

Most aquatic plants applied to ecological restoration have demonstrated a clonal growth pattern. The risk-spreading strategy plays a crucial role in facilitating clonal plant growth under external environmental stresses via clonal integration. However, the effects of different concentrations of nanoplastics (NPs) on the growth traits of clonal aquatic plants are not well understood. Therefore, this study aimed to investigate the impact of NPs exposure on seedlings of parent plants and connected offspring ramets. A dose response experiment (0.1, 1, and 10 mg L-1) showed that the growth of Eichhornia crassipes (water hyacinth) was affected by 100 nm polystyrene nanoplastics after 28 days of exposure. Tracer analysis revealed that NPs are accumulated by parent plants and transferred to offspring ramets through stolon. Quantification analysis showed that when the parent plant was exposed to 10 mg L-1 NPs alone for 28 days, the offspring ramets contained approximately 13 ± 2 µg/g NPs. In the case of connected offspring ramets, leaf and root biomass decreased by 24%-51% and 32%-51%, respectively, when exposed to NP concentrations ranging from 0.1 to 10 mg L-1. Excessive enrichment of NPs had a detrimental effect on the photosynthetic system, decreasing the chlorophyll content and nonphotochemical quenching. An imbalance in the antioxidant defense systems, which were unable to cope with the oxidative stress caused by NP concentrations, further damaged various organs. The root system can take up NPs and then transfer them to the offspring through the stolon. Interference effects of NPs were observed in terms of root activity, metabolism, biofilm composition, and the plant's ability to purify water. However, the risk-spreading strategy employed by parent plants (interconnected offspring ramets) offered some relief from NP-induced stress, as it increased their relative growth rate by 1 to 1.38 times compared to individual plants. These findings provide substantial evidence of the high NP enrichment capacity of E. crassipes for ecological remediation. Nevertheless, we must also remain aware of the environmental risk associated with the spread of NPs within the clonal system of E. crassipes, and contaminated cloned individuals need to be precisely removed in a timely manner to maintain normal functions.