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Heavy metal pollution has been a global concern and key points of environmental pollution prevention and control due to the growing problems of urbanization and industrialization. Rapidly and correctly apportioning sources of heavy metal is still a great challenge because of the stability of source fingerprint and complex interaction of multiple contaminants and sources. In this study, we perform a combination of optimization of pollution source fingerprint and source apportionment through jointly utilizing two machine classification and screening methods for characterizing the pollution sources of heavy metal in the sediments of an urban river and its surrounding soils. Dominance-based rough set model (DRS), content optimization tools, and multivariate curve resolution-alternating least squares model (MCR-WALS) were employed to screen representative pollution source samples, optimize pollution source fingerprint, and apportion the potential sources of heavy metals, respectively. Further, Support vector machine (SVM) was adopted to correspondence analysis results and pollution fingerprint based on the factor characteristics for achieving source apportionment accurately. Results showed that the pollution source pollution source fingerprints optimized by DRS and optimization tools are more representative and stable, and the results obtained by SVM and MCR-WALS are more accurate comparing with traditional methods. As whole, source apportionment suggested that printing and dyeing, chemical, electroplating, metal processing were the main origins of heavy metals in this area and the proportions of them in sediment and soil pollution sources were 67.05% and 28.43%, respectively. Besides, coal combustion was also the main sources of heavy metal pollution in soils, accounting about 34.16%. Results of the study can advance our knowledge to better understand the characterization of heavy metal pollution in the peri-urban ecosystem and to design effective targeted strategies for reducing heavy metal pollution diffusion. [Display omitted] • A combination of fingerprint screening and source apportionment was performed. • Characteristics and source-sink relationship of heavy metals in the river-soil system was studied. • Source apportionment was executed using MLR-WALS combined with SVM. • Multiple complex industrial activities were the dominant same type contributor of heavy metals in the river sediments. [ABSTRACT FROM AUTHOR]

Contaminated sites have been recognized as posing serious comprehensive social and environmental issues and have earned worldwide attention. China is becoming one of the largest contaminated sites remediation markets in the world and the contaminated sites in northeastern China need to rehabilitate urgently. However, remediation planning is often hindered by high financial costs resulting from incomplete assessments of pollution and inappropriate remediation plans. In-depth contaminated site assessments can provide the necessary baseline data for remediation alternatives screening. Therefore, risk assessments and remediation decisions will play crucial roles in the rehabilitation and reconstruction of contaminated sites in China. The main objectives of this study were to present a novel method for health risk assessment (HRA) and to demonstrate a multicriteria decision analysis (MCDA) based on this method to select the most suitable remediation alternatives of groundwater and to prioritize management of contaminated site. To demonstrate the HRA and MCDA processes, a typical contaminated site in Longtan, Jilin province, China, was used. The results of this research indicated that Benzene (PhH) and 1,2-Dichloroethylene (1,2-DCE) were the main organic pollutants and the vanillin plant in the north of the site was main pollution source. Pollution migrated from the north to the south and the health risk range in winter was significantly greater than in summer. Four remediation alternatives were proposed on the basis of the HRA results. The MCDA results showed that PRB was the most suitable technology for integrating the relevant environmental, social, economic, and technical aspects required for remediation. This study may help responsible agencies to strengthen local risk-based program screening frameworks for contaminated sites, to promote reconstruction projects, and to increase local public confidence of contaminated sites remediation. ga1 • Health risk assessment was combined with groundwater remediation alternatives screening. • Health risk zones in contaminated site were delineated. • Screening of groundwater remediation alternatives was executed using MCDA with Monte Carlo simulation. • PRB were identified as the optimal technology for low-level groundwater contamination remediation. [ABSTRACT FROM AUTHOR]

Increasing anthropogenic contamination poses a significant threat to groundwater security. Identifying potential contamination sources and apportioning their corresponding contributions are of vital importance for the prevention of contamination and management of groundwater resources. In this study, principal component analysis (PCA), modified grey relational analysis (MGRA), absolute principal component score-multiple linear regression (APCS-MLR), and positive matrix factorization (PMF) receptor modeling technologies were employed to evaluate the groundwater quality and apportion the potential contamination sources in the Lalin river basin, a main grain production district in the northeast of China. The contamination assessment with PCA and MGRA suggested that the groundwater in Lalin river basin was polluted due to human activities. The PCA method identified five and four potential contamination sources in wet and dry seasons, respectively, and the main sources were basically same. The APCS-MLR and PMF methods apportioned the source contributions to each groundwater quality variable. The final results showed that agricultural sources including waste water, agrochemicals and fertilizers were identified as the main sources of groundwater contamination both in wet and dry seasons. In addition, groundwater management strategies learned from the advanced experiences were discussed to protect the groundwater system in that region. Unlabelled Image • Groundwater contamination, risk and sources in Lain River Basin were studied in wet and dry seasons. • Agricultural activities was recognized as the significant pollution sources in the groundwater of Lalin River Basin. • The contributions of potential contamination sources of groundwater were comparative studied by APCS-MLR and PMF. • Some suggestions are presented to promote groundwater management. [ABSTRACT FROM AUTHOR]

Heavy metals (HMs) in lake sediments have aroused long-term attention due to their persistent threat to the lake ecosystems. Study into the pollution characteristics and potential sources of HMs in lakes, especially those heavily influenced by human activities, can give some insights to prevent and control the environmental risks of HMs. Lake Tai is the China's third largest freshwater lake but has been a drastic example of water pollution in recent decades. Here, we systematically investigated the characterization of pollution, risk and sources of HMs in the sediments of Lake Tai and its surrounding soils using several methods and tools. Specifically, a total of 46 sediments and 578 soils were collected from the study area, and geochemical approaches (geo-accumulation index and enrichment factor) and pollution indexes were jointly used to reveal the contamination characteristics of HMs. Meanwhile, the potential ecological risk index and probabilistic model of health risk assessment were employed to understand the environmental risk of HMs. Further, absolute principle component score-multiple linear regression and positive matrix factorization models were comparatively applied to apportion the sources of HMs. Results showed that various metals including Cd, Cr, As, Hg, Pb, and Cu appeared contamination level in varying degrees both in the sediments and soils. In particular, Cd, As and Hg were identified as the significant contaminants and presented moderate ecological risk. As a whole, the health risk levels of metals were acceptable. Source apportionment suggested that industrial discharge, agricultural activities, atmospheric deposition and natural source were the potential origins of HMs in this area. Among them, anthropogenic activities were the largest dominator of HMs with contribution of >75%. The study will advance our knowledge on HMs in lake and its surrounding soils and provide reference for policy maker to design migration strategies for protecting the lake ecosystems. Unlabelled Image • Contamination risk and sources of HMs in the sediments of Lake Tai were studied. • Cd, As and Hg were recognized as the significant contaminants. • Contamination risk of HMs in the sediments of Lake Tai was higher than surrounding soils. • Anthropogenic activities were the largest dominator of HMs with contributions of >75%. [ABSTRACT FROM AUTHOR]

The peri-urban rivers are one of the critical interfaces between urban-rural symbiotic ecosystems and appear to be a reservoir of antibiotic resistance genes (ARGs) in the environment. To prevent the transmission risks of ARGs between peri-urban river and human, it is essential to explore the prevalence and source of ARGs in the environment for designing potential mitigation strategies. In this study, we focused on the characterization and source-tracking of ARGs in the sediments of a typical peri-urban river in Beijing, Chaobai River. Twenty-seven ARGs frequently reported in the environment, and two integrons (intI1 and intI2) were detected using high-throughput quantitative PCR. The profile of bacterial community was determined by performing 16S rRNA gene sequencing. Meanwhile, crAssphage , a novel recently-discovered DNA bacteriophage, was employed for tracking the contribution of human fecal pollution to the prevalence of ARGs. Results showed that the targeted ARGs were detected widely in the sediments of Chaobai River. Relatively, the abundances of ARGs in downstream were higher than those in the upstream, likely suggesting a gradient impact of anthropogenic activities along the river. Remarkably, the int1 gene was correlated significantly with most of the ARGs and might be the key factor influencing the shaping of ARGs in the river sediments. However, no significant correlations were observed between the ARGs and selective pressure factors, including antibiotics and metals. Of the identified 1039 genera, Escherichia - Shigella , Bacteroides , Arcobacter , Dechloromonas and Pseudomonas were the top most abundant organisms. Microbial source tracking based on the crAssphage annotation suggested that human sewage might be one of the potential sources of resistance bacteria in the river sediments. The study can advance our knowledge about ARGs in the peri-urban river and provides a management reference for ARG pollution control. Unlabelled Image • A variety of ARGs were widely detected in the sediments of a peri-urban river. • Class 1 integron potentially affected the shaping of ARGs in the river. • A gradient in anthropogenic impacts on ARGs was observed along the river. • CrAssphage-based metagenomics approach was used for microbial source tracking. • Human fecal pollution was identified as potential source of ARGs in the river. [ABSTRACT FROM AUTHOR]

Abstract The over-use of antibiotics causes growing concerns about human health risks induced by increasing rates of antimicrobial resistance. Riverine systems are considered generally as a natural reservoir of antibiotic resistance genes (ARGs). In this study, several methods including high-throughput sequencing-based metagenomics approach, statistical analysis and network analysis were applied jointly to characterize the wide-spectrum profile of ARGs in the sediments of an urban river in Beijing. Furthermore, contribution of human activities for the presence of ARGs was identified through comparative studies on the metagenomic profiling of ARGs between the river sediments and pristine niches (remote Antarctic soils and deep sea sediments). In total, 442 ARG subtypes belonging to 22 ARG types were detected in the human-impacted river sediments with an abundance range of 1.1 × 10−1–8.1 × 10−1 copy of ARG per copy of 16S-rRNA gene. The most abundant and diverse ARGs were commonly associated with antibiotics that have been extensively used in that area, likely indicating the spread of ARGs in river environments because of the selective pressure resulting from antibiotic use. As a whole, anthropogenic activities were the dominant contributor of major ARG types, for example, occupying 100% for sulfonamide-ARGs, 97% for beta-lactam-ARGs, 94% for aminoglycoside-ARGs and 64% for tetracycline-ARGs. This study provides insights into the role of human activities in accelerating the dissemination and proliferation of ARGs in urban river environment and draws attention to controlling the use and discharge of antibiotics for protection of public health. Graphical abstract Unlabelled Image Highlights • Characterization of ARGs in Chaobai River was investigated using metagenomics. • 442 ARG subtypes belonging to 22 ARG types were detected in the river sediments. • Bacitracin- and sulfonamide-ARGs were the most abundant types. • 95 ARG subtypes were shared by the river sediments and pristine environments. • Anthropogenic activities contributed >95% for sulfonamide and beta-lactam ARGs. [ABSTRACT FROM AUTHOR]

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated. • A source-oriented ecological risk assessment model was proposed. • The Zn, Cu and Fe were identified as priority trace metals for water ecological risk control. • The concentrations of these trace metals in surface water demonstrated significant spatial variations. • The copper production activities are the largest contributor of ecological risk source in Le'an River. [ABSTRACT FROM AUTHOR]

Here, a new integrated methodology framework has been proposed for source apportionment and source-oriented risk evaluation, and applied to identify the characteristics, sources and health risks of PAHs in the soils of a typical cold region in Northeastern China. To this end, a large-scale data set containing 1780 soil samples and 16 priority PAHs has been collected from the study area. Two advanced receptor models, positive matrix factorization (PMF) and multivariate curve resolution-weighted alternating least-squares (MCR-WALS), have been comparatively employed to apportion the pollution sources of soil PAHs, with the help of a set of modified literature PAH source fingerprints. Further, the apportionment results have been incorporated into a probabilistic incremental lifetime cancer risk model for assessing the source-specific health risk of soil PAHs. Notably, the PMF and MCR-WALS models have apportioned essentially same results. The coal combustion and gasoline engine are identified as the main contributors of soil PAHs, with contributions of 57.9–58.1% and 25.2–22.2%, respectively. The health risks posed by PAHs in the soils are negligible for both adult and children; relatively, source-oriented risk assessment shows coal combustions make the largest contribution to the total risk of PAHs (56.1%), followed by gasoline engine (22.5%) and coke oven (21.4%). [Display omitted] • A new integrated framework has been proposed for characterizing sources and risks of PAHs. • Apportionment results have been used for assessing source-specific health risk of PAHs. • The MCR-WALS model has apportioned essentially same results with PMF. • Coal combustion, gasoline engine and coke oven are the main pollution sources of PAHs. • Coal combustion has made the largest contribution to the total risk of PAHs (56.1%). [ABSTRACT FROM AUTHOR]

Colon cancer is one of the most common types of cancer and more than 80% of colon cancer cases are associated with Wnt-β-catenin signaling activation. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a multi-functional long non-coding RNA that is overexpressed in many types of cancers, including colon cancer. In this study, MALAT1 and β-catenin were found to be overexpressed in tumor samples from 62 patients with colon cancer. A positive correlation was identified between MALAT1 levels and β-catenin protein levels in tumors. MALAT1 was found to upregulate β-catenin protein levels in HCT116 and LOVO cells without changing the mRNA expression levels. β-catenin degradation was confirmed to be upregulated in MALAT1 -knockdown cells and inhibited in cells overexpressing MALAT1 overexpressing. MALAT1 was then identified as a negative regulator of GSK-3β; it did so via promotion of H3K27 trimethylation of the promoter region. In conclusion, MALAT1 is an oncogene in colon cancer, which inhibits β-catenin degradation by upregulating H3K27 trimethylation and repressing GSK-3β expression. • MALAT1 is overexpressed in colon cancer. • MALAT1 is positively correlated with β-catenin protein levels. • MALAT1 inhibits β-catenin protein degradation by repressing GSK-3β expression. • MALAT1 inhibits GSK-3β expression by upregulating H3K27 trimethylation. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance is a growing public health concern, and environment is regarded as an important reservoir and dissemination route for antibiotic resistance genes (ARGs). To prevent and control ARG pollution, it is essential to correctly disentangle source-sink relationship of ARGs in the environment. However, accurately apportioning sources of ARGs is still a big challenge due to the complex interaction of multiple sources and contaminants in the environment with changing dynamics. In this study, we addressed this problem and focused on identifying the potential sources of ARGs in a peri-urban river by jointly utilizing two novel microbial source tracking methods. To attain the objective, sediment/water samples were collected from the peri-urban river and four ARG-associated ecotypes including effluents of sewage treatment plants (STPs), STP influent, chicken manures and pig manures. The high-throughput profilings of ARGs and microbial taxa in the river sediments and the four ecotypes were comprehensively characterized in combination of shotgun sequencing and metagenomic assembly analysis. CrAssphage , a recently-discovered DNA bacteriophage, was employed to track the impact of human fecal pollution on ARGs in the river sediments. Further, SourceTracker, a machine-learning classification tool, was used for quantifying the contributions of potential sources to ARGs in the river sediments based on the metagenomic signatures of ARGs and microbial taxa. In total, 888 ARG subtypes belonging to 29 ARG types were detected across all samples, including mcr-1 and a range of carbapenemases types. Statistical analyses suggested different ecotypes generally had distinct profiles of both ARGs and microbial taxa, while the ARG compositions were significantly correlated with the microbial community. Source tracking with crAssphage showed the presence of ARGs in the river sediments might be largely impacted by the extent of human fecal pollution, which was also confirmed by the analyses of SourceTracker that the discharge from STPs was the largest contributor of ARGs (81.6–92.1%) and microbes (49.3–68.1%) in the river sediments. Results of the study can help us to better understand the characterization of ARGs in the peri-urban ecosystem and to design effective prevention and control strategies for reducing ARG dissemination. • 888 ARG subtypes belonging to 29 ARG types were detected in the study. • CrAssphage was a good marker for tracking human fecal pollution in the study area. • Effluent of STPs was the largest contributor of ARGs in the river sediments. [ABSTRACT FROM AUTHOR]