Fertilization regulates global thresholds in soil bacteria.

Global patterns in soil microbiomes are driven by non-linear environmental thresholds. Fertilization is known to shape the soil microbiome of terrestrial ecosystems worldwide. Yet, whether fertilization influences global thresholds in soil microbiomes remains virtually unknown. Here, utilizing optimized machine learning models with Shapley additive explanations on a dataset of 10,907 soil samples from 24 countries, we discovered that the microbial community response to fertilization is highly dependent on environmental contexts. Furthermore, the interactions among nitrogen (N) addition, pH, and mean annual temperature contribute to non-linear patterns in soil bacterial diversity. Specifically, we observed positive responses within a soil pH range of 5.2-6.6, with the influence of higher temperature (>15°C) on bacterial diversity being positive within this pH range but reversed in more acidic or alkaline soils. Additionally, we revealed the threshold effect of soil organic carbon and total nitrogen, demonstrating how temperature and N addition amount interacted with microbial communities within specific edaphic concentration ranges. Our findings underscore how complex environmental interactions control soil bacterial diversity under fertilization.

Data-Driven Insights into the Contamination of Polycyclic Aromatic Hydrocarbons in Marine Bays.

The synthesis of polycyclic aromatic hydrocarbon (PAH) data allows us to quantify and gain insights into the spatiotemporal dynamics of PAH contamination in marine bays. Here, a data synthesis framework was developed to understand data-driven insights into the spatiotemporal levels, compositional profiles, and potential sources of PAHs in water and sediment of marine bays. PAHs were detected in 69 bays worldwide, with contamination hotspots located in Asian bays. PAH concentrations in pre-2000 were significantly lower than those in the 2000s and post-2010, while the dominant species in water and sediment were 2-3 ring and 4-6 ring PAHs, respectively. The composition patterns of PAHs included 2-3 ring, 3-5 ring, and 4-5 ring dominant categories, but no significant distance decay relationship was found in the composition similarity due to international energy trade. Temporal dynamic patterns of concentrations included Descending-, Ascending-, and Inverted V-type, whereas over longer time spans, the pattern is more similar to the Inverted V-type owing to the reductions in emission intensity. PAHs were derived from both petrogenic and pyrolytic sources, with combustion from both coal and petroleum being the dominant source. These data-driven discoveries provide quantitative insights into the spatiotemporal patterns in the concentration and composition of PAHs, contributing to the mitigation of PAH contamination.

Wastewater Discharge Transports Riverine Microplastics over Long Distances.

Wastewater discharge from wastewater treatment plants continuously pumps microplastics into rivers, yet their transport distances within these waterways remain unknown. Herein, we developed a conceptual framework by synthesizing the microplastic data from the Yangtze River Basin to evaluate its transport distances, quantifying a significant spatial dependence between large-scale wastewater discharge and riverine microplastics (p < 0.05). The presence of microplastics at a specific sampling site could be attributed to wastewater discharge within a large-scale range spanning >1000 km upstream, encompassing a substantial portion equivalent to one-third of the Yangtze River Basin. The dominance analysis indicated that the contribution of wastewater discharge in rivers with higher discharge (>100 m3/s) to riverine microplastic pollution exceeded 65% within the Yangtze River Basin. The spatial dependence framework of riverine microplastics on wastewater discharge advances our prior understanding of the prevention and control of riverine microplastics by demonstrating that such pollution is not limited to nearby environmental factors.

Distance-decay equations of antibiotic resistance genes across freshwater reservoirs.

Distance-decay (DD) equations can discern the biogeographical pattern of organisms and genes in a better way with advanced statistical methods. Here, we developed a data Compilation, Arrangement, and Statistics framework to advance quantile regression (QR) into the generation of DD equations for antibiotic resistance genes (ARGs) across various spatial scales using freshwater reservoirs as an illustration. We found that QR is superior at explaining dissemination potential of ARGs to the traditionally used least squares regression (LSR). This is because our model is based on the 'law of limiting factors', which reduces influence of unmeasured factors that reduce the efficacy of the LSR method. DD equations generated from the 99th QR model for ARGs were 'Sall = 90.03e-0.01Dall' in water and 'Sall = 92.31e-0.011Dall' in sediment. The 99th QR model was less impacted by uneven sample sizes, resulting in a better quantification of ARGs dissemination. Within an individual reservoir, the 99th QR model demonstrated that there is no dispersal limitation of ARGs at this smaller spatial scale. The QR method not only allows for construction of robust DD equations that better display dissemination of organisms and genes across ecosystems, but also provides new insights into the biogeography exhibited by key parameters, as well as the interactions between organisms and environment.

Significant regional disparities in riverine microplastics.

Research on riverine microplastics has gradually increased, highlighting an area for further exploration: the lack of extensive, large-scale regional variations analysis due to methodological and spatiotemporal limitations. Herein, we constructed and applied a comprehensive framework for synthesizing and analyzing literature data on riverine microplastics to enable comparative research on the regional variations on a large scale. Research results showed that in 76 rivers primarily located in Asia, Europe, and North America, the microplastic abundance of surface water in Asian rivers was three times higher than that in Euro-America rivers, while sediment in Euro-American rivers was five times more microplastics than Asia rivers, indicating significant regional variations (p < 0.001). Additionally, based on the income levels of countries, rivers in lower-middle and upper-middle income countries had significantly (p < 0.001) higher abundance of microplastics in surface water compared to high-income countries, while the opposite was true for sediment. This phenomenon was preliminarily attributed to varying levels of urbanization across countries. Our proposed framework for synthesizing and analyzing microplastic literature data provides a holistic understanding of microplastic disparities in the environment, and can facilitate broader discussions on management and mitigation strategies.

Microplastic accumulation in groundwater: Data-scaled insights and future research.

Given that microplastics (MPs) in groundwater have been concerned for risks to humans and ecosystems with increased publications, a Contrasting Analysis of Scales (CAS) approach is developed by this study to synthesize all existing data into a hierarchical understanding of MP accumulation in groundwater. Within the full data of 386 compiled samples, the median abundance of MPs in Open Groundwater (OG) and Closed Groundwater (CG) were 4.4 and 2.5 items/L respectively, with OG exhibiting a greater diversity of MP colors and larger particle sizes. The different pathways of MP entry (i.e., surface runoff and rock interstices) into OG and CG led to this difference. At the regional scale, median MP abundance in nature reserves and landfills were 17.5 and 13.4 items/L, respectively, all the sampling points showed high pollution load risk. MPs in agricultural areas exhibited a high coefficient of variation (716.7%), and a median abundance of 1.0 items/L. Anthropogenic activities at the regional scale are the drivers behind the differentiation in the morphological characteristics of MPs, where groundwater in residential areas with highly toxic polymers (e.g., polyvinylchloride) deserves prolonged attention. At the local scale, the transport of MPs is controlled by groundwater flow paths, with a higher abundance of MP particles downstream than upstream, and MPs with regular surfaces and lower resistance (e.g., pellets) are more likely to be transported over long distances. From the data-scaled insight this study provides on the accumulation of MPs, future research should be directed towards network-based observation for groundwater-rich regions covered with landfills, residences, and agricultural land.

Harnessing the runoff reduction potential of urban bioswales as an adaptation response to climate change.

Nature-based solutions (NbS), including China's Sponge City Program (SCP), can address the challenges urban communities face due to surface runoff and flooding. The current capacity of SCP facilities in urban environments falls short of meeting the demands placed on communities by climate change. Bioswales are a form of SCP facility that plays an important role in reducing surface runoff by promoting infiltration. This study assesses the potential of SCP facilities to reduce runoff in urban communities under climate change using the storm water management model. The study site in Ningbo, China, was used to evaluate the potential role of bioswales in reducing runoff risks from climate change. We found that bioswales were most effective in scenarios when rainfall peaks occurred early and were less effective in right-skewed rainfall events. The overall performance of SCP facilities was similar across all climate scenarios. To maintain the current protection level of SCP facilities, bioswales would need to cover at least 4% of the catchment area. These findings from Ningbo provide a useful method for assessing NbS in other regions and indicative values for the increase in the bioswale coverage needed to adapt to climate change.

Characterising global antimicrobial resistance research explains why One Health solutions are slow in development: An application of AI-based gap analysis.

The global health crisis posed by increasing antimicrobial resistance (AMR) implicitly requires solutions based a One Health approach, yet multisectoral, multidisciplinary research on AMR is rare and huge knowledge gaps exist to guide integrated action. This is partly because a comprehensive survey of past research activity has never performed due to the massive scale and diversity of published information. Here we compiled 254,738 articles on AMR using Artificial Intelligence (AI; i.e., Natural Language Processing, NLP) methods to create a database and information retrieval system for knowledge extraction on research perfomed over the last 20 years. Global maps were created that describe regional, methodological, and sectoral AMR research activities that confirm limited intersectoral research has been performed, which is key to guiding science-informed policy solutions to AMR, especially in low-income countries (LICs). Further, we show greater harmonisation in research methods across sectors and regions is urgently needed. For example, differences in analytical methods used among sectors in AMR research, such as employing culture-based versus genomic methods, results in poor communication between sectors and partially explains why One Health-based solutions are not ensuing. Therefore, our analysis suggest that performing culture-based and genomic AMR analysis in tandem in all sectors is crucial for data integration and holistic One Health solutions. Finally, increased investment in capacity development in LICs should be prioritised as they are places where the AMR burden is often greatest. Our open-access database and AI methodology can be used to further develop, disseminate, and create new tools and practices for AMR knowledge and information sharing.

Influence of watershed characteristics and human activities on the occurrence of organophosphate esters related to dissolved organic matter in estuarine surface water.

Organophosphate esters (OPEs) are widespread in aquatic environments and pose potential threats to ecosystem and human health. Here, we profiled OPEs in surface water samples of heavily urbanized estuaries in eastern China and investigated the influence of watershed characteristics and human activities on the spatial distribution of OPEs related to dissolved organic matter (DOM). The total OPE concentration ranged from 22.3 to 1201 ng/L, with a mean of 162.6 ± 179.8 ng/L. Chlorinated OPEs were the predominant contaminant group, accounting for 27.4-99.6 % of the total OPE concentration. Tris(2-chloroisopropyl) phosphate, tris(1,3-dichloro-2-propyl) phosphate, and tributyl phosphate were the dominant compounds, with mean concentrations of 111.2 ± 176.0 ng/L, 22.6 ± 21.5 ng/L, and 14.8 ± 14.9 ng/L, respectively. Variable OPE levels were observed in various functional areas, with significantly higher concentrations in industrial areas than in other areas. Potential source analysis revealed that sewage treatment plant effluents and industrial activities were the primary OPE sources. The total OPE concentrations were negatively correlated to the mean slope, plan curvature, and elevation, indicating that watershed characteristics play a role in the occurrence of OPEs. Individual OPEs (triisobutyl phosphate, tris(2-butoxyethyl) phosphate, tris(2-chloroethyl) phosphate, and tricresyl phosphate) and Σalkyl-OPEs were positively correlated to the night light index or population density, suggesting a significant contribution of human activity to OPE pollution. The co-occurrence of OPEs and DOM was also observed, and the fluorescence indices of DOM were found to be possible indicators for tracing OPEs. These findings can elucidate the potential OPE dynamics in response to DOM in urbanized estuarine water environments with intensive human activities.

A lack of focus on data sharing, stakeholders, and economic benefits in current global green infrastructure planning.

Green infrastructure (GI) is increasingly popular in solving urban environmental challenges and enhancing ecosystem services. Yet the research status and challenges of GI planning have not been comprehensively benchmarked to date. We explored the GI types, actions, goals, and spatiotemporal characteristics of GI planning cases worldwide based on the available literature. The challenges of GI planning were also investigated by the cases included in this manuscript. Additionally, the urban governance solutions to address these challenges were proposed. We found that multi-type GI planning is the most popular. Data sharing, stakeholder participation, economic benefits and research funding for GI planning research were generally inadequate, although they have improved trend over time. Multiple-goal GI planning frequently has higher levels of data sharing, stakeholder participation and economic benefits than GI planning that just takes into account one purpose. We conclude that the future transformation of GI planning requires efficient data sharing mechanisms, effective co-design among stakeholders, systematic business models, and available research funding.

Linking pharmaceutical residues to dissolved organic matter and aquatic bacterial communities in a highly urbanized bay.

Pharmaceuticals are causing environmental concerns associated with their widespread distribution in aquatic ecosystems. The environmental fate and behavior of pharmaceutical residues are related to dissolved organic matter and bacterial communities, both of which are strongly influenced by human activities. However, the relationships among pharmaceutical pollution, dissolved organic matter pool, and bacterial community structure under the pressure of human activities are still unclear, especially in highly urbanized bay areas. In this study, we investigated the occurrence and distribution of 35 pharmaceuticals in a typical urbanized bay (Hangzhou Bay) in Eastern China, and analyzed their relationships with dissolved organic matter and aquatic bacterial community structure. The target pharmaceuticals were ubiquitously detected in surface water samples, with their concentrations ranging from undetectable to 263 ng/L. The detected pharmaceuticals were mostly sulfonamides, macrolides, antidepressants, and metabolites of stimulants. Significant positive correlations were observed between the concentrations of pharmaceuticals and the intensity of human activities. Strong correlations also emerged between the concentration of antidepressants and the speed of urban expansion, as well as between the concentration of cardiovascular drugs and the population density or nightlight index. Three fluorescent components (protein-like C1, terrestrial humic-like C2, protein tryptophan-like C3) were significantly positively correlated with the total concentration of pharmaceuticals. Pharmaceutical pollution reshaped aquatic bacterial communities, based on the close correlation observed between pharmaceutical concentration and bacterial community structure. The results elucidate the potential dynamics of dissolved organic matter pool and aquatic bacterial communities in response to pharmaceutical pollution in urbanized bay ecosystems.

Evaluation of Lactate Dehydrogenase and Alkaline Phosphatase as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram.

Background: Tumor proliferation is frequently accompanied by aberrant enzyme production. We aim to investigate the potential predictive value of both plasma alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) in patients with HCC and to develop a nomogram to assess the prognosis of HCC. Methods: The trial involved 2327 patients between May 2015 and March 2022. Within 7 days of enrollment, the levels of ALP and LDH were measured, and their association with survival was assessed. And we had developed and validated a new nomogram based on ALD and ALP. Results: Using X-tile software, the optimal cut-off values were determined to be ALP = 172 U/L and LDH = 241 U/L. The high ALP (≥ 172), LDH (≥ 241), and ALP/LDH (≥ 0.91) groups had lower median overall survival (mOS) than low ALP (< 172), LDH (< 241), and ALP/LDH (< 0.91) groups (all p < 0.001). In addition, elevated ALP and LDH levels are independent negative prognostic indicators. Moreover, we established that the area under the curve (AUC) values of the predicted 1-, 2-, and 3-year survival rates of receiver operating characteristic curve (ROC) based on the nomogram were 0.79, 0.77, and 0.74, respectively. In addition, the calibration curves and decision curve analyses (DCA) demonstrated that this model possessed strong predictive capability. Conclusion: ALP, LDH and ALP/LDH can be employed as biomarkers for predicting the prognosis of HCC. Furthermore, the nomograph based on ALH and ALP demonstrates good HCC prediction performance. For HCC patients with high ALH or ALP or ALP/LDH, close surveillance program and adjuvant therapy should be considered.

Data-driven discoveries on widespread contamination of freshwater reservoirs by dominant antibiotic resistance genes.

The propagation of antibiotic resistance genes (ARGs) in freshwater reservoirs threatens ecosystem security and human health, and has attracted increasing attention. A series of recent research articles on ARGs provides a unique opportunity for data-driven discoveries in this emerging field. Here, we mined data from a total of 290 samples from 60 reservoirs worldwide with a data-driven framework (DD) developed to discover geographical distribution, influencing factors and pollution hotspots of ARGs in freshwater reservoirs. Most data came from Asia and Europe where nine classes of ARGs were most frequently detected in reservoirs with multi-drug resistance and sulfonamide resistance genes prevailing. Factors driving distribution of reservoir ARGs differed between reservoir waters and sediments, and interactions among these factors had linear or nonlinear enhancement effects on the explanatory power of ARG distribution. During the cold season, small-sized reservoir waters rich in organic carbon, mobile genetic elements (MGEs) and antibiotics had a higher pollution potential of ARGs; during the spring drought, sediments in large reservoirs located in densely populated areas were more conducive to dissemination of ARGs due to their richness in antibiotics and MGEs. Thus, distribution pattern of ARG pollution hotspots in reservoir waters and sediments varies greatly depending on the differences of internal and external factors. From the "One Health" perspective, this widespread contamination of freshwater reservoirs by ARGs we discovered through the DD framework should be a push to promote integrated research across regions and disciplines. Especially the human - food-chain - ecosystem interface needs an improved understanding of ARG contamination mechanisms and targeted monitoring and evaluation systems should be developed to maintain all ecosystem services in freshwater reservoirs as well as to safeguard human health.

Widespread occurrence of microplastics in marine bays with diverse drivers and environmental risk.

Microplastic contamination in the sediment of marine bays has attracted widespread attention, whereas the distribution, sedimentation, morphology and risk of microplastics at regional scale remain poorly understood. By introducing a data mining framework into microplastic research, we compiled a microplastic dataset of 649 samples from 24 bays to enhance the understanding of geographical difference and drivers, transfer, composition profile and environmental risk of sedimental microplastics. Microplastic abundance varied from 0.72 to 1963.96 items/kg dry weight, with higher concentrations mainly occurring in East Asian bays. The spatial pattern in abundance was driven by the river plastic emissions, aquaculture production and hydrodynamic condition. A significantly positive correlation between microplastic abundance in water and sediment was found, and microplastic sedimentation was related to polymer density, hydrodynamic conditions and sediment properties. The dominant shape and polymer of sedimental microplastics were fiber and polypropylene, respectively, and the similarity of microplastic composition decreased with increasing geographical distance. The environmental risks of microplastics were partitioned into three classes (Rank II-Rank IV) with a two-dimensional assessment system considering the bioavailability and toxicity of microplastics, and Asian bays were identified as potential high-risk areas. To reduce the environmental risk of sedimental microplastics in bays, priority should be given to the removal of microfibers, and control measures depend on the risk classes and dominant polymers. Microplastic abundance and composition were significantly affected by methodological choices regarding sampling, pretreatment and identification, suggesting a unified methodology is essential to further enhance our knowledge on the distribution and risk of microplastics in marine bays.

PD-L1 expression on circulating tumor cells can be a predictive biomarker to PD-1 inhibitors combined with radiotherapy and antiangiogenic therapy in advanced hepatocellular carcinoma.

Aim: A programmed death 1 (PD-1) inhibitor coupled with radiotherapy and antiangiogenic therapy is a potential therapeutic strategy for advanced hepatocellular carcinoma (HCC). We aimed to determine if circulating tumor cells (CTCs) positive for programmed death-ligand 1 (PD-L1) could be employed as a predictive biomarker in HCC patients receiving triple therapy. Methods: In this study, HCC patients received a PD-1 inhibitor in combination with intensity-modulated radiotherapy (IMRT) and antiangiogenic therapy. Following IMRT, the PD-1 inhibitor was administrated once every 3 weeks, while the antiangiogenic drug was given once a day. Treatment was continued until the disease progressed. Two mL of peripheral blood was collected at baseline, 1 month, and 3 months after treatment for CTC enrichment using the CytoSorter® system with a CytoSorter™ CTC PD-L1 Kit (Watson Biotech., China). Result: A total of 47 HCC patients receiving the triple therapy were enrolled in this study. Patients with < 2 PD-L1+ CTCs at baseline had a higher objective response rate (ORR) and longer overall survival (OS) than those with ≥ 2 PD-L1+ CTCs (56.5% vs. 16.7%, p = 0.007; not reach vs. 10.8 months, p = 0.001, respectively). The count of PD-L1+ CTCs was found to be an independent predictive biomarker of OS. Furthermore, the objective response was more likely to be achieved in patients with a dynamic decrease in PD-L1+ CTC counts at 1 month after treatment. Conclusions: Our study demonstrated that PD-L1+ CTCs could be a predictive biomarker for HCC patients receiving PD-1 inhibitors in combination with IMRT and antiangiogenic therapy.

Heat-shock protein 90α is a potential prognostic and predictive biomarker in hepatocellular carcinoma: a large-scale and multicenter study.

BACKGROUND: Although the diagnostic value of plasma heat-shock protein 90α (HSP90α) in hepatocellular carcinoma (HCC) has been previously reported, the causal effect of the plasma HSP90α levels on HCC prognosis remains largely unclear. To this extent, we sought to assess whether the plasma HSP90α acts as a prognostic factor for HCC patients. METHODS: A total of 2150 HCC patients were included in this retrospective study between August 2016 and July 2021. Plasma HSP90α levels were tested within a week before treatment and their association with prognosis was assessed. RESULTS: An optimal cutoff value of 143.5 for the HSP90α based on the overall survival (OS) was determined using the X-tile software. HCC patients with HSP90α < 143.5 ng/mL (low HSP90α) before and after propensity score matching (PSM) indicated longer median OS (mOS) relative to those with HSP90α ≥ 143.5 ng/mL (high HSP90α) (37.0 vs. 9.0 months, p < 0.001; 19.2 vs. 9.6 months, p < 0.001; respectively). In addition, the high HSP90α plasma level is an independent poor prognostic factor for OS in HCC patients. In our subgroup analysis, including the supportive care group, surgery group, transarterial chemoembolization (TACE) group, adjuvant TACE group, an immune checkpoint inhibitor (ICI) plus targeted therapy group, and TACE plus ICI group, the high HSP90α group demonstrated better OS compared to the low HSP90α group. Moreover, in the supportive care, TACE, ICI plus targeted therapy, TACE plus ICI groups, and high HSP90α levels were also an independent poor prognostic factors for OS. CONCLUSIONS: Our study confirmed that the plasma HSP90α level can be used as a prognostic biomarker for HCC.

Co-driving factors of tidal effect on the abundance and distribution of antibiotic resistance genes in the Yongjiang Estuary, China.

The unreasonable use of antibiotics and the transmission of antibiotic resistance genes (ARGs) induced by antibiotics have led to a large number of ARGs entered the water environment, which seriously threatened human health and environmental safety. The estuarine aquatic environment connects with inland rivers and sea and is frequently influenced by human activities. This study aims to reveal the occurrences and abundances of ARGs and bacterial community composition by high-throughput quantitative PCR including 296 primers and high-throughput sequencing in the tide rising and ebbing of surface water in the Yongjiang Estuary, China. The results showed that there were a large number of ARGs and mobile genetic elements (MGEs) detected in the rising tide and ebb tide water bodies. The numbers of detected ARGs in each sample at rising and ebb tide ranged from 16 to 77 and 61 to 88, respectively, and the absolute abundance ranges were 1.69 × 104-1.69 × 109 copies/L and 3.18 × 103-2.57 × 109 copies/L, respectively. Obvious tidal distribution characteristics of ARGs were showed. Most of ARGs conferred resistance to multidrug, aminoglycosides and sulfanilamides. Proteobacteria, Actinobacteria and Bacteroidetes were the dominantly bacterial phylum in the Yongjiang Estuary. Network analysis results indicated that multi-genera were identified as possible ARGs hosts, and they carried more than two types of ARGs genes. Partial least squares path modeling further revealed that MGEs and bacterial community composition were the most important driving factors. The results of the study can provide the corresponding scientific basis for the diffusion and control of ARGs in estuaries.

Evolving framework of studies on global gulf ecosystems with Sustainable Development Goals.

Gulf ecosystems provide many beneficial services to humanity and play a key role in achieving the Sustainable Development Goals (SDGs). However, the sustainability of gulf ecosystems has been severely threatened by climatic and anthropogenic stresses. Using network analysis of article records downloaded from Web of Science, we summarize the current research framework of gulf ecosystems via the perspectives of research themes, interdisciplinarity, and international collaborations. Research themes involve nutrient and eutrophication, biodiversity, mangrove and sediment pollution, and ecosystem service and climate change. Nevertheless, these themes usually focus on gulf ecosystems themselves with little consideration of their connectivity with other ecosystems. Interdisciplinarity has remained mostly within natural sciences while international collaborations exist mainly between developed and developing countries and among developed countries. Combined with the SDGs, we propose the future research framework where research themes should consider the impacts of terrestrial and freshwater ecosystems on gulf ecosystems at the watershed scale. Interdisciplinarity between natural and social and management sciences needs to be promoted by utilizing the advantages of data sciences. Collaborations with developing countries led by China, Mexico, Brazil, and India need to be strengthened. The evolved research framework could offer decision support for stakeholders to manage gulf ecosystems and achieve the SDGs.

Distribution, transfer, ecological and human health risks of antibiotics in bay ecosystems.

Antibiotics have been widely detected in bay ecosystems, yet little is known regarding their distribution, composition, sources, ecological and human health risks at the regional scale. We developed a systematic framework to mine data from existing publications and compiled an antibiotic concentration-based dataset containing 439 samples from 30 bays, and compared antibiotics across bays and matrices (water, sediment, and biota). Antibiotic concentrations varied considerably between bays, with hotspots occurring in East Asia. The main categories of antibiotics in waters included sulfonamide and macrolide, while tetracycline, quinolone, and macrolide antibiotics were prevalent in sediments. The main sources of antibiotics in bays included sewage treatment plant effluent, domestic sewage, agriculture runoff, and discharges from mariculture activities. Antibiotics with high ecological risks mainly included sulfamethoxazole, erythromycin, clarithromycin, and oxytetracycline. Erythromycin posed a considerable risk to human health, and the human health risks presented by other antibiotics were negligible. Regional variations of concentrations correspond to the uneven geographic consumption of antibiotics and their removal rate during wastewater treatment. Differences in antibiotics' composition between matrices are associated mainly with the physicochemical properties of antibiotics (e.g., molecular structure, solubility, and stability) and the content of total organic carbon, metal ions, chlorophyll a, and clay minerals in the sediments. To reduce the ecological and human health implications, priority should be given to the removal of erythromycin, sulfamethoxazole, oxytetracycline, and clarithromycin, with a special focus on their treatment in the Asian bay areas.

Global meta-analysis of microplastic contamination in reservoirs with a novel framework.

Microplastic contamination in reservoirs is receiving increasing attention worldwide. However, a holistic understanding of the occurrence, drivers, and potential risks of microplastics in reservoirs is lacking. Building on a systematic review and meta-analysis of 30 existing publications, we construct a global microplastic dataset consisting of 440 collected samples from 43 reservoirs worldwide which we analyze through a framework of Data processing and Multivariate statistics (DM). The purpose is to provide comprehensive understanding of the drivers and mechanisms of microplastic pollution in reservoirs considering three different aspects: geographical distribution, driving forces, and ecological risks. We found that microplastic abundance varied greatly in reservoirs ranging over 2-6 orders of magnitude. Small-sized microplastics (< 1 mm) accounted for more than 60% of the total microplastics found in reservoirs worldwide. The most frequently detected colors, shapes, and polymer types were transparent, fibers, and polypropylene (polyester within aquatic organisms), respectively. Geographic location, seasonal variation and land-use type were main factors influencing microplastic abundance. Detection was also dependent on analytical methods, demonstrating the need for reliable and standardized methods. Interaction of these factors enhanced effects on microplastic distribution. Microplastics morphological characteristics and their main drivers differed between environmental media (water and sediment) and were more diverse in waters compared to sediments. Similarity in microplastic morphologies decreased with increasing geographic distance within the same media. In terms of risks, microplastic pollution and potential ecological risk levels are high in reservoirs and current policies to mitigate microplastic pollution are insufficient. Based on the DM framework, we identified temperate/subtropical reservoirs in Asia as potential high-risk areas and offer recommendations for analytical methods to detect microplastics in waters and sediments. This framework can be extended and applied to other multi-scale and multi-attribute contaminants, providing effective theoretical guidance for reservoir ecosystems pollution control and management.