Microbial metabolism influences microplastic perturbation of dissolved organic matter in agricultural soils.

An estimated 258 million tons of plastic enter the soil annually. Joining persistent types of microplastic (MP), there will be an increasing demand for biodegradable plastics. There are still many unknowns about plastic pollution by either type, and one large gap is the fate and composition of dissolved organic matter (DOM) released from MPs as well as how they interact with soil microbiomes in agricultural systems. In this study, polyethylene MPs, photoaged to different degrees, and virgin polylactic acid MPs were added to agricultural soil at different levels and incubated for 100 days to address this knowledge gap. We find that, upon MP addition, labile components of low aromaticity were degraded and transformed, resulting in increased aromaticity and oxidation degree, reduced molecular diversity, and changed nitrogen and sulfur contents of soil DOM. Terephthalate, acetate, oxalate, and L-lactate in DOM released by polylactic acid MPs and 4-nitrophenol, propanoate, and nitrate in DOM released by polyethylene MPs were the major molecules available to the soil microbiomes. The bacteria involved in the metabolism of DOM released by MPs are mainly concentrated in Proteobacteria, Actinobacteriota, and Bacteroidota, and fungi are mainly in Ascomycota and Basidiomycota. Our study provides an in-depth understanding of the microbial transformation of DOM released by MPs and its effects of DOM evolution in agricultural soils.

Microfiber Hotspots' Association with Ships in a Remote Port before and during Covid-19.

During monthly water quality monitoring of Norwegian coastal waters, the sea surface waters off Brønnøysund, a remote port in Norway, exhibited an unexpectedly high abundance of microfibers. We further conducted monitoring of microplastics and microfibers from the surface waters off the city before and during the Covid-19 pandemic. Analysis of the microfiber characteristics, which were primarily comprised of cellulosic and polyester fibers, revealed similarities with those found in the global ocean, but at concentrations that were 1-4 orders of magnitude higher, with the maximum concentration reaching 491 n/L (0.34 mg/L). Source apportionment of microfibers using multivariate analyses based on simultaneous water chemistry data showed positive correlations with ships. Contrary to previous assumptions that marine microfibers were derived from land-based sources, our findings revealed that gray water discharge from ships significantly contributed to microfibers in the oceans. The demonstrated causations using path modeling between microfibers, gray water, shipping, and noncargo shipping activities call for urgent research and regulatory actions toward addressing plastic pollution in the UN Decade of Ocean Science.

Constructing Z-scheme 1D/2D heterojunction of ZnIn2S4 nanosheets decorated WO3 nanorods to enhance Cr(VI) photocatalytic reduction and rhodamine B degradation.

Photocatalysis has been vastly employed as a feasible and efficient strategy for the removal of environmental pollutants. In this study, a well-designed core-shell heterojunction of WO3 decorated with ZnIn2S4 nanosheets were fabricated under mild in-situ conditions, and fabricated processes were systematically investigated with different fabrication durations. The coupling of WO3 and ZnIn2S4 (ZIS) resulted in a Z-scheme mechanism for charge carrier transfer, holding the respective redox capacity. The as-prepared 1D/2D WO3@ZIS heterostructure displayed the highest removal efficiency within 30 min for 25 mg L-1 Cr(VI), 89.3 and 29.7 times higher than pure WO3 and ZnIn2S4. 1D/2D WO3@ZIS remained excellently stable after 5 cycling experiments. Moreover, 40 mg L-1 RhB could be degraded within 50 min. The broad and short photogenerated electron transportation path is guaranteed by the 1D/2D and Z-scheme charge separation mechanism. It efficiently prevented photo-generated charge carriers from recombination, resulting in a longer carrier lifespan and better photocurrent responses than that of pure ones. This photocatalytic system showed promising results and also provides a framework for an efficient system for photocatalysis with potential for environmental application.

Scavenging of reactive oxygen species effectively reduces Pseudomonas aeruginosa biofilms through disrupting policing.

Biofilm formation is likely to contribute greatly to antibiotic resistance in bacteria and therefore the efficient removal of bacterial biofilms needs addressing urgently. Here, we reported that the supplement of non-inhibitory concentration of N-acetyl-L-cysteine (NAC), a common reactive oxygen species (ROS) scavenger, can significantly reduce the biomass of mature Pseudomonas aeruginosa biofilms (corroborated by crystal violet assay and laser scanning confocal microscopy). 1 mM NAC increased the cheater (ΔlasR mutant) frequency to 89.4 ± 1.5% in the evolved PAO1 after the 15-day treatment. Scavenging of ROS by NAC induced the collapse of P. aeruginosa biofilms, but it did not alter quorum sensing-regulated genes expression (e.g., hcnC and cioAB) and hydrogen cyanide production. The replenishment of public good protease contributed to the recovery of biofilm biomass, indicating the role of disrupting policing in biofilm inhibition. Furthermore, 7 typical ROS scavengers (e.g., superoxide dismutase, catalase and peroxidase, etc.) also effectively inhibited mature P. aeruginosa biofilms. This study demonstrates that scavenging of ROS can promote the selective control of P. aeruginosa biofilms through policing disruption as a targeted biofilm control strategy in complex water environments.

Distribution, Source Apportionment and Risk Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) in Surface Sediments at the Basin Scale: A Case Study in Taihu Basin, China.

As a systematic research at basin scale, this study investigated the spatial distribution, source apportionment and ecological risks of eighteen polycyclic aromatic hydrocarbons (PAHs) in surface sediments at different functional regions (rivers, lakes and reservoirs) from Taihu basin. Results showed that the mean values of 18 PAHs (defined as ∑18PAHs) in river sediments (1277 ng/g) was much higher than those observed in lake sediments (243 ng/g) and reservoir sediments (134 ng/g). The accumulation of PAHs in river sediments was largely impacted by the local social-economic development and energy consumption. The positive matrix factorization (PMF) and isomer ratios analysis of PAHs suggest that relative contributions to PAHs in sediments were 15% for gasoline and heavy oil combustion, 9% for oil spills, 30% for coal combustion, 23% for traffic source, and 23% for diagenetic source. Ecological risk assessment based upon risk quotient (RQ) method indicated that sediments at Taihu basin have suffered moderate risk of PAHs.

Facilitated transport of microplastics and nonylphenol in porous media with variations in physicochemical heterogeneity.

Nonylphenol (Noph) has garnered worldwide concern as a typical endocrine disruptor due to its toxicity, estrogenic properties, and widespread contamination. To better elucidate the interaction of Noph with ubiquitously existing microplastics (MPs) and the potential interdependence of their transport behaviors, batch adsorption and column experiments were conducted, paired with mathematical modeling. Compared with sand, MPs and soil colloids show stronger adsorption affinity for Noph due to the formation of hydrogen bonding and the larger numbers of interaction sites that are available on solid surfaces. Limited amount of soil-colloid coating on sand grains significantly influenced transport behaviors and the sensitivity to solution chemistry. These coatings led to a monotonic increase in Noph retention and a nonmonotonic MPs retention in single systems because of the altered physicochemical properties. The mobility of both MPs and Noph was enhanced when they coexisted, resulting from their association, increased electrostatic repulsion, and competition on retention sites. Limited release of MPs and Noph (under reduced ionic strength (IS) and increased pH) indicated strong interactions in irreversible retention. The retention and release of Noph were independent of IS and solution pH. A one-site model with a blocking term and a two-site kinetic model well described the transport of MPs and Noph, respectively. Our findings highlight the essential roles of coexisting MPs and Noph on their transport behaviors, depending on their concentrations, IS, and physicochemical properties of the porous media. The new knowledge from this study refreshes our understanding of the co-transport of MPs and organic contaminants such as Noph in the subsurface.

Reduction of antibiotic resistance genes (ARGs) in swine manure-fertilized soil via fermentation broth from fruit and vegetable waste.

The issue of growing increase of antibiotic resistance genes (ARGs) in manure-fertilized soil needs urgently addressing. In this study, fermentation broth from fruit and vegetable waste was prepared to reduce ARG abundance in swine manure-fertilized soils. With a six-month field experiment, we found that swine manure-fertilized soil had significantly higher ARG abundance than soil applied with chemical fertilizer. As expected, the homemade fermentation broth significantly reduced ARG abundance in swine manure-fertilized soil, possibly through the decrease of abundance of Actinomyces, in which there was a 48.0%, 51.9%, and 66.7% decrease in the abundance of Nocardioides, Streptomyces, and Nonomuraea, respectively. With the bacteriostatic experiment, we observed that fermentation broth (5 mL/L) significantly inhibited the growth and metabolism in Actinomycetes spp. and Nocardioides sp., in terms of ATPase and PDH activity. These findings confirmed that the inhibition of Actinobacteria, some of the most dominant ARG hosts, was one of the main mechanisms responsible for the decrease in ARG abundance in fermentation broth-treated soil. This study provides field-scale evidence of a feasible strategy for controlling farmland ARG pollution, which is of utmost importance for soil health in the context of sustainable agriculture.

Polycyclic aromatic hydrocarbons in fine road dust from a coal-utilization city: Spatial distribution, source diagnosis and risk assessment.

Coal combustion can release large amounts of polycyclic aromatic hydrocarbons (PAHs), which persist in various environment matrices (e.g., road dust) and hence cause the carcinogenic risk to human health. In this study, an exhaustive characterization of road dust samples coupling their physicochemical characteristics and stable isotope compositions (δ13C and δ15N) was conducted to evaluate the source, level, spatial distribution, and carcinogenic risk of PAHs in a typical coal-utilization city. Concentrations of Σ16 PAHs ranged from 605.5 to 25,374.3 ng/g with a mean concentration of 4083.0 ng/g. Pollution levels of sites around the coal-fired power plant (Zone 1) were significantly higher than those in other zones (p < 0.05). PAH concentration showed significant correlations with both C and N fractions (p < 0.01). Compositions of δ13C and δ15N in road dust coupled to principal component analysis and the partitions and diagnostic ratios of PAHs contributed to associating road dust to several local sources of contamination. Coal combustion and vehicular exhaust were major sources of PAHs around the power plant and urban area. Results of incremental lifetime cancer risk showed 81.5% of all sampling sites suffered potential risk (>10-6) for both adults and children, while children around the power plant suffered the highest risk. Despite the estimation of only potential risk being posed by PAHs in road dust, human exposure to the various environmental matrices, scientific and systematic assessment of carcinogenic risks by PAHs in the total environment warrants further investigations.

Effects of chemical and natural ageing on the release of potentially toxic metal additives in commercial PVC microplastics.

Various chemical substances, such as potentially toxic trace metals, are used as plastic additives to improve the performance of polymers and extend the service life of plastic products. However, these added trace metals are likely released from plastic into the environment when the plastic becomes a pollutant, although the process is poorly understood. In this study, chemical ageing of commercial polyvinyl chloride (PVC) microplastics using hydrogen peroxide (H2O2) and natural ageing of PVC that had been added to an alkaline paddy soil were undertaken to evaluate the potential release of trace metals from PVC. Enhanced release of trace metals from PVC with the increasing H2O2 concentrations was observed, in which the released Pb was 1-2 orders of magnitude higher than other metals (p < 0.01). The released Cr, Ni, Pb, Cu, Zn, Cd and Mn accounted for 87.37%, 79.27%, 22.02%, 20.93%, 17.06%, 15.11%, and 11.02% of their total concentrations (0.28 ± 0.03, 0.08 ± 0.01, 13.67 ± 0.18, 1.07 ± 0.02, 2.20 ± 0.18, 0.05 ± 0.00 and 1.26 ± 0.08 mmol kg-1) in PVC after ageing with 30% H2O2, respectively. Compared with the control treatment without PVC addition, the concentrations of CaCl2-extractable Cu, Mn, Ni, Pb, and Zn in the soil treated with 5% PVC are significantly increased after incubation for 60 days (p < 0.01). In conclusion, chemical and natural ageing have the potential to lead to the release of Cu, Mn, Ni, Pb, and Zn from the commercial PVC into aquatic and terrestrial environments.

Interaction with teichoic acids contributes to highly effective antibacterial activity of graphene oxide on Gram-positive bacteria.

Graphene oxide (GO) has high-efficient antibacterial activity to diverse pathogenic bacteria. However, the detailed antibacterial mechanism of GO is not fully clear. Herein the antibacterial properties of GO against model Gram-positive (Gram+) (Staphylococcus aureus and Staphylococcus epidermidis) and Gram-negative (Gram-) bacteria (Pseudomonas aeruginosa and Escherichia coli) were compared by plate count method. Results showed that 4 mg/L of GO induced the mortality of Gram+ and Gram- bacteria by > 99% and < 25%, respectively. GO had greater adsorption affinity to teichoic acids, the unique components existing in the cell wall of Gram+ bacteria, mainly via π-π interaction. The adsorption efficiency of teichoic acids was 27 times higher than that of peptidoglycan when they were simultaneously exposed to 100 mg/L GO. The superior adsorption of teichoic acids onto GO increased one order of magnitude of atlA expression, the autolysin related gene. As a result, these accelerated bacterial death by hydrolyzing peptidoglycan in cell walls. Exogenous addition of 50 mg/L teichoic acids could impair 4-5 fold of antibacterial activity of GO against S. aureus. These new findings illuminate the antibacterial mechanism of GO against Gram+ bacteria, which paves the way for the further application of graphene-based materials in water disinfection and pathogen control.

Sorption of pharmaceuticals and personal care products on soil and soil components: Influencing factors and mechanisms.

The sorption of pharmaceuticals and personal care products (PPCPs) on soil and soil components makes an important contribution to the fate, migration and bioavailability of PPCPs. Previous reviews have mostly focused on the sorption of PPCPs on single soil components (e.g., minerals and soil organic matter). However, the sorption of PPCPs within the whole soil system has not been systematically analyzed. This paper reviews the recent progress on PPCP sorption on soil and soil components. We have evaluated the sorption of a wide range of PPCPs in research fields that are usually considered in isolation (e.g., humic acids (HAs), montmorillonite, kaolinite, and goethite), and established a bridge between PPCPs and sorbent. The sorption mechanisms of PPCPs, e.g., cation exchange, surface complexation, electrostatic interaction and hydrogen bonding, are discussed and critically evaluated. We also assessed the influence of environmental factors (pH, ionic strength, organic matter and temperature) on sorption. This review summarizes the knowledge of PPCPs sorption on soil gained in recent years, which can provide new strategies for solving the problem of antibiotic pollution.

Contrasting effects of microplastics on sorption of diazepam and phenanthrene in soil.

Microplastics have attracted extensive attention regarding their role in the cycling of organic pollutants in aquatic environments. However, the influence of microplastics on the sorption of organic pollutants in soil is unclear. Herein, we investigated the sorption of polar diazepam and nonpolar phenanthrene to two soils (Inceptisol and Oxisol). Batch sorption experiments were used to evaluate the effect of polyethylene (PE), polypropylene (PP), and polystyrene (PS) microplastics at addition rates of 0.1%, 1%, and 10% (w/w). The addition of microplastics significantly decreased the overall sorption of diazepam at 10%, and increased the sorption of phenanthrene at 1%, while the effects were negligible at other addition rates. Decreased sorption of diazepam was attributed to its lower sorption affinity to microplastics than to soil. Microplastics, even at 0.1%, substantially decreased the relative distribution of phenanthrene in soil, particularly for PE in the Oxisol with lower foc. The sorption affinity of phenanthrene followed the order PE > soil organic carbon (SOC) > PP > PS, suggesting that PE can be a significant sink of phenanthrene in contaminated soils. Overall, microplastics can change the sorption of diazepam and phenanthrene to soil and therefore affect their mobility and environmental risk in soil ecosystems.

Image Clustering via Deep Embedded Dimensionality Reduction and Probability-Based Triplet Loss.

Image clustering is more challenging than image classification. Without supervised information, current deep learning methods are difficult to be directly applied to image clustering problems. Image clustering needs to deal with three main problems: 1) the curse of dimensionality caused by highdimensional image data; 2) extracting the effective image features; 3) combining feature extraction, dimensionality reduction and clustering. In this paper, we propose a new clustering framework called Deep Embedded Dimensionality Reduction Clustering (DERC) via Probability-Based Triplet Loss, which effectively solves the above issues. To the best of our knowledge, the DERC is the first framework that effectively combines image embedding, dimensionality reduction, and clustering into the image clustering process. We also propose to incorporate a novel probability-based triplet loss measure to retrain the DERC network as a unified framework. By integrating the reconstruction loss and the probability-based triplet loss, we can improve the image clustering accuracy. Extensive experiments show that our proposed methods outperform state-of-the-art methods on many commonly used datasets.

Occurrence, risk and influencing factors of polycyclic aromatic hydrocarbons in surface soils from a large-scale coal mine, Huainan, China.

Coal is one of the most important fossil fuels for energy, but it can cause serious polycyclic aromatic hydrocarbon (PAH) pollution to the environment. In this work, the distribution, sources, influencing factors, and risk assessment of PAHs were studied in a soil of typical coal resource city, Huainan, China. The total concentration of 16 PAHs classified by USEPA in 47 soils ranged from 109.94 to 1105.30 ng/g with a mean concentration of 528.06 ng/g. The PAH concentration was higher in soil of this area than most of the agricultural, urban and industrial soils and lower than some coal mine and coal-fired power plant areas in the world. The principal component analysis (PCA) and diagnostic ratios demonstrated that PAHs in soils were mainly from the coal combustion and refined petroleum products. The total organic carbon (TOC, p < 0.01) and black carbon (BC, p < 0.01) can significantly influence PAH inventories in soils, particularly for PAHs with high molecular weight. In addition, the significantly positive correlations between PAHs in feed coal (p < 0.05), fly ash (p < 0.01), particulate matter (PM1-2.5 and PM2.5-10, p < 0.01) and PAHs in soils revealed that the emission sources and deposition processes were also the main factors affecting PAH contents in soils. The estimated values of incremental lifetime cancer risk (ILCR) for children and adults were higher than 10-4 at all sampling sites, suggesting high carcinogenic risks for local residents, and the most important exposure route for PAHs was dermal absorption. These findings are valuable for assessing the health risk of PAHs in soils around typical coal mine and coal-fired power plants and highlight the urgency of taking actions to control and reduce the carcinogenic risks for local residents.

Operation-aware Neural Networks for user response prediction.

User response prediction makes a crucial contribution to the rapid development of online advertising system and recommendation system. The importance of learning feature interactions has been emphasized by many works. Many deep models are proposed to automatically learn high-order feature interactions. Since most features in advertising systems and recommendation systems are high-dimensional sparse features, deep models usually learn a low-dimensional distributed representation for each feature in the bottom layer. Besides traditional fully-connected architectures, some new operations, such as convolutional operations and product operations, are proposed to learn feature interactions better. In these models, the representation is shared among different operations. However, the best representation for each operation may be different. In this paper, we propose a new neural model named Operation-aware Neural Networks (ONN) which learns different representations for different operations. Our experimental results on two large-scale real-world ad click/conversion datasets demonstrate that ONN consistently outperforms the state-of-the-art models in both offline-training environment and online-training environment.

Distribution of arsenic and its biotransformation genes in sediments from the East China Sea.

Microbial transformation of arsenic (As) plays a key role in As biogeochemical cycling and affects the mobility, bioavailability, and toxicity of As. This study aims to investigate the accumulation of As in marine sediments at different water depths in the East China Sea and reveal the abundance and diversity of the aioA, arrA, arsC, and arsM genes through quantitative real-time polymerase chain reaction (qPCR) and high-throughput sequencing. Results showed that the As content in sediments ranged from 5.53 mg kg-1 to 17.70 mg kg-1, which decreased with water depth. Abundant As biotransformation genes with low diversity were identified in these sediments, of which arsM and arrA were the most abundant. Significant positive correlation exists between the arsM and arrA gene abundance and between arsC and aioA, indicating the co-occurrence of the As biotransformation genes in microbes in marine sediments. Metagenomics analysis revealed that arsM gene was mainly distributed in Alphaproteobacteria, Solibacteres, Deltaproteobacteria, Clostridia, and Bacilli in these sediments. Among the sediment properties, total N, total S, C/N, and TOC were important factors that shaped the abundance profile of the genes involved in As transformation. This study provides a picture of As biotransformation genes in marine sediments from the East China Sea, which may affect As transformation and the ultimate fate of As in a marine environment.

Locally linear SVMs based on boundary anchor points encoding.

In this paper, we propose a locally linear classifier based on boundary anchor points encoding (LLBAP) to achieve the efficiency of linear SVM and the power of kernel SVM. LLBAP partitions linearly non-separable data into approximately linearly separable parts based on boundary point scanning and local coding. Each part of data is solved by a linear SVM. Experiments on large-scale benchmark datasets demonstrate that the proposed method is more efficient than kernel SVM in both training and testing phases; its efficiency and classification accuracy also outperform other locally linear classifiers on those benchmark datasets.

Sorption of pentachlorophenol and phenanthrene by humic acid-coated hematite nanoparticles.

Hematite nanoparticles (NPs) exist naturally and ubiquitously in soil, and they are always associated with soil organic matter by forming organic-inorganic complexes. In this work, hematite NPs coated with peat humic acid (HApeat) and soil humic acid (HAsoil) were chosen as sorbents for hydrophobic organic contaminants (HOCs) to simulate the sorption processes in soil. Ionizable pentachlorophenol (PCP) and non-ionizable phenanthrene (PHE) were selected as representative HOCs. Compared with sorption isotherms of uncoated hematite NPs, the coating of HA onto the surface of hematite NPs substantially increased its sorption affinity for PCP and PHE by about 1-2 orders of magnitude, and the increasing degree was positively correlated to the HA content. These phenomena emphasized the dominant role of HA in the sorption process. The reduced polarity and the introduction of functional groups contributed to the enhanced sorption of HOCs on HA-coated hematite NPs. Furthermore, HApeat-hematite NPs showed higher sorption affinity for both PCP and PHE than HAsoil-hematite NPs, which was mainly due to the lower polarity and higher hydrophobicity of HApeat-hematite NPs. The sorption of PCP and PHE on HA-coated hematite NPs was inhibited obviously with increasing pH values and the pH effect on PCP sorption was more significant than that of PHE, due to the deprotonation of functional groups within adsorbed HA, the loose structure of adsorbed HA and the dissociation of PCP. Our findings elucidated the mechanisms involved in HOCs sorption processes by HA-hematite NPs and provided a theoretical basis for environmental remediation with natural NPs (e.g., hematite NPs).