Impact of four surfactants on the uptake of per- and polyfluoroalkyl substances (PFAS) by red fescue grass.

Per- and polyfluoroalkyl substances (PFAS) pose great risks to human health and the ecosystem, necessitating effective remediation strategies such as phytoremediation. Surfactants, due to their ability to increase the bioavailability of hydrophobic contaminants, are considered as potential agents to improve phytoremediation for PFAS. In this research, we explored the impact of four surfactants (sodium dodecyl sulfate (SDS), rhamnolipid, Triton X-100, and Glucopone 600 CS UP) on plant growth and the uptake of PFAS by red fescue over 110 days. The results showed that while surfactants at lower concentrations did not negatively affect plant growth, the highest dose (2,500 mg/kg) significantly reduced the dry weight of plant shoots. Although none of the four surfactants led to an increased overall removal efficiency of ∑PFAS by red fescue over 110 days, SDS did enhance the uptake of PFAS compounds with long carbon chain lengths. With SDS addition at 2,500 mg/kg, the average fold increases of long chain PFAS removal were 1.99 for perfluorooctanoic acid (PFOA), 2.44 for perfluorononanoic acid (PFNA), 2.11 for perfluorodecanoic acid (PFDA), 1.52 for perfluoroundecanoic acid (PFUnA), 1.88 for perfluorohexanesulphonic acid (PFHxS), and 2.97 for perfluorooctanesulfonic acid (PFOS). The research indicated that using surfactants, such as SDS at appropriate doses could improve phytoremediation effectiveness in mitigating long-chain PFAS, which is a known challenge in soil remediation.

This study proposed an approach to accelerate plant uptake and removal of long chain PFAS. The improved removal of long chain PFAS coupled with less plant biomass by amending soil with SDS at a proper dose potentially increases the attractiveness of phytoremediation.

Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks.

In recent years, the Chinese government has actively pursued the implementation of its 'dual-carbon' strategy, concurrently establishing a national carbon emissions trading market. Accurate carbon price forecasts have become essential for policymakers and investors involved in related initiatives. Nevertheless, influenced by the interaction of various information sources, carbon trading prices exhibit non-linear and non-stationary characteristics, posing challenges for accurate prediction. Current research, centered around deep learning models, predominantly emphasizes intricate network structures, optimisation algorithms, and data decomposition. However, these models face a developmental bottleneck in extracting carbon price features and efficiently leveraging multi-source information. Consequently, novel ideas and methodologies are imperative. This study focuses on the Hubei and Guangdong regional carbon markets as research subjects. It develops a prediction framework based on a generative adversarial network model to capture the time-series change characteristics of carbon trading prices and the condition matrix. First, a generator prediction model is used to obtain the input matrix features and extract the time series features through a complex network to predict the carbon price data at the next moment using a fully connected layer. Second, a discriminator is utilised to distinguish between the actual values and the predicted values. The generator and the discriminator undergo continuous iterative training and alternate optimisation. This process aims to bring the generated prediction distributions closer to the actual sample data, resulting in more accurate final predictions. The empirical results convincingly show that the proposed model achieves unparalleled forecasting precision in both markets. The proposed model demonstrates the lowest MAE (0.804 and 0.839), lowest MAPE (0.023 and 0.018), lowest RMSE (1.174 and 1.383), and highest R2 (0.971 and 0.989) across both markets, indicating superior predictive accuracy. Additionally, the proposed model consistently outshines traditional forecasting approaches across one-step, five-step, and ten-step forecasts, affirming its robustness and universal applicability in modelling carbon trading price series. The findings suggest that this study can aid policymakers in optimizing the carbon pricing system. Furthermore, it offers a reference for policymakers to comprehensively leverage external factors, such as regulating traditional energy prices, leveraging international carbon market experiences, and monitoring economic dynamics. This comprehensive strategy can streamline the exploration and management of carbon price fluctuations, ultimately strengthening the carbon market's risk control system.

A chromosome-level genome assembly of radish (Raphanus sativus L.) reveals insights into genome adaptation and differential bolting regulation.

High-quality radish (Raphanus sativus) genome represents a valuable resource for agronomical trait improvements and understanding genome evolution among Brassicaceae species. However, existing radish genome assembly remains fragmentary, which greatly hampered functional genomics research and genome-assisted breeding. Here, using a NAU-LB radish inbred line, we generated a reference genome of 476.32 Mb with a scaffold N50 of 56.88 Mb by incorporating Illumina, PacBio and BioNano optical mapping techniques. Utilizing Hi-C data, 448.12 Mb (94.08%) of the assembled sequences were anchored to nine radish chromosomes with 40 306 protein-coding genes annotated. In total, 249.14 Mb (52.31%) comprised the repetitive sequences, among which long terminal repeats (LTRs, 30.31%) were the most abundant class. Beyond confirming the whole-genome triplication (WGT) event in R. sativus lineage, we found several tandem arrayed genes were involved in stress response process, which may account for the distinctive phenotype of high disease resistance in R. sativus. By comparing against the existing Xin-li-mei radish genome, a total of 2 108 573 SNPs, 7740 large insertions, 7757 deletions and 84 inversions were identified. Interestingly, a 647-bp insertion in the promoter of RsVRN1 gene can be directly bound by the DOF transcription repressor RsCDF3, resulting into its low promoter activity and late-bolting phenotype of NAU-LB cultivar. Importantly, introgression of this 647-bp insertion allele, RsVRN1In-536 , into early-bolting genotype could contribute to delayed bolting time, indicating that it is a potential genetic resource for radish late-bolting breeding. Together, this genome resource provides valuable information to facilitate comparative genomic analysis and accelerate genome-guided breeding and improvement in radish.

Prediction of Plant Uptake and Translocation of Engineered Metallic Nanoparticles by Machine Learning.

Machine learning was applied to predict the plant uptake and transport of engineered nanoparticles (ENPs). A back propagation neural network (BPNN) was used to predict the root concentration factor (RCF) and translocation factor (TF) of ENPs from their essential physicochemical properties (e.g., composition and size) and key external factors (e.g., exposure time and plant species). The relative importance of input variables was determined by sensitivity analysis, and gene-expression programming (GEP) was used to generate predictive equations. The BPNN model satisfactorily predicted the RCF and TF in both hydroponic and soil systems, with an R2 higher than 0.8 for all simulations. Inclusion of the initial ENP concentration as an input variable further improved the accuracy of the BPNN for soil systems. Sensitivity analysis indicated that the composition of ENPs (e.g., metals vs metal oxides) is a major factor affecting RCF and TF values in a hydroponic system. However, the soil organic matter and clay contents are more dominant in a soil system. The GEP model (R2 = 0.8088 and 0.8959 for RCF and TF values) generated more accurate predictive equations than the conventional regression model (R2 = 0.5549 and 0.6664 for RCF and TF values) in a hydroponic system, which could guide the sustainable design of ENPs for agricultural applications.

Environmental factors affecting degradation of perfluorooctanoic acid (PFOA) by In2O3 nanoparticles.

Nanophotocatalysts have shown great potential for degrading poly- and perfluorinated substances (PFAS). In light of the fact that most of these catalysts were studied in pure water, this study was designed to elucidate effects from common environmental factors on decomposing and defluorinating perfluorooctanoic acid (PFOA) by In2O3 nanoparticles. Results from this work demonstrated that among the seven parameters, pH, sulfate, chloride, H2O2, In2O3 dose, NOM and O2, the first four had statistically significant negative effects on PFOA degradation. Since PFOA is a strong acid, the best condition leading to the highest PFOA removal was identified for two pH ranges. When pH was between 4 and 8, the optimal condition was: pH = 4.2; sulfate = 5.00 mg/L; chloride = 20.43 mg/L; H2O2 = 0 mmol/L. Under this condition, PFOA decomposition and defluorination were 55.22 and 23.56%, respectively. When pH was between 2 and 6, the optimal condition was: pH = 2; sulfate = 5.00 mg/L; chloride = 27.31 mg/L; H2O2 = 0 mmol/L. With this condition, the modeled PFOA decomposition was 97.59% with a defluorination of approximately 100%. These predicted results were all confirmed by experimental data. Thus, In2O3 nanoparticles can be used for degrading PFOA in aqueous solutions. This approach works best when the target contaminated water contains low concentrations of NOM, sulfate and chloride and at a low pH.

Environmental Risks of Nano Zerovalent Iron for Arsenate Remediation: Impacts on Cytosolic Levels of Inorganic Phosphate and MgATP2- in Arabidopsis thaliana.

The use of nano zerovalent iron (nZVI) for arsenate (As(V)) remediation has proven effective, but full-scale injection of nZVI into the subsurface has aroused serious concerns for associated environmental risks. This study evaluated the efficacy of nZVI treatment for arsenate remediation and its potential hazards to plants using Arabidopsis thaliana grown in a hydroponic system. Biosensors for inorganic phosphate (Pi) and MgATP2- were used to monitor in vivo Pi and MgATP2- levels in plant cells. The results showed that nZVI could remove As(V) from growth media, decrease As uptake by plants, and mitigate As(V) toxicity to plants. However, excess nZVI could cause Pi starvation in plants leading to detrimental effects on plant growth. Due to the competitive adsorption of As(V) and Pi on nZVI, removing As(V) via nZVI treatment at an upstream site could relieve downstream plants from As(V) toxicity and Pi deprivation, in which case 100 mg/L of nZVI was the optimal dosage for remediation of As(V) at a concentration around 16.13 mg/L.

Impact of Nanoparticle Surface Properties on the Attachment of Cerium Oxide Nanoparticles to Sand and Kaolin.

Soil texture has been found to be a critical factor in regulating the fate and transport of cerium oxide nanoparticles (CeONPs) in the terrestrial environment. However, the underlying mechanisms for the interactions between CeONPs and different components of soil are still poorly understood. The attachment of CeONPs onto two typical components of soil (sand and kaolin) in batch experiments were investigated to provide insights into the retention and bioavailability of CeONPs in soil. Surface properties of CeONPs, including surface charge and surface coating condition, had strong impacts on the interactions between CeONPs and soil particles. Positively charged CeONPs [CeONPs(+)] displayed the greatest attachment onto kaolin, whereas the negatively charged CeONPs [CeONPs(-)] showed poorest attachment onto sand. The attachment of CeONPs onto kaolin was significantly greater than onto sand, irrespective of surface charge. Homoaggregation of CeONPs increased the size of CeONPs on the surface of sand and kaolin. Extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) calculations agreed with the experimental observations that surface charge and coating condition of CeONPs played a vital role in the homoaggregation and adsorption of CeONPs. For CeONPs(-) coated with polyvinylpyrrolidone (PVP), the steric repulsion between soil particles and CeONPs increases rapidly with the increase of maximum surface concentration of PVP. Adsorption isothermal fittings indicated that the adsorption of CeONPs onto sand and kaolin can be properly described by the Dubinin-Radushkevich isotherm. The results obtained in this study are crucial for the understanding of the fate and transport of engineered nanomaterials in the environment.

Uptake, Accumulation, and in Planta Distribution of Coexisting Cerium Oxide Nanoparticles and Cadmium in Glycine max (L.) Merr. .

Agricultural soils are likely to be polluted by both conventional and emerging contaminants at the same time. Understanding the interactions of coexisting engineered nanoparticles (ENPs) and trace elements (a common source of abiotic stress) is critical to gaining insights into the accumulation of these two groups of chemicals by plants. The objectives of this study were to determine the uptake and accumulation of coexisting ENPs and trace elements by soybeans and to gain insights into the physiological mechanisms resulting in different plant accumulation of these materials. The combinations of three cadmium levels (0 [control] and 0.25 and 1 milligrams per kilogram of dry soil) and two CeO2 NPs concentrations (0 [control] and 500 milligrams per kilogram of dry soil) were investigated. Measurements of the plant biomass and physiological parameters indicated that CeO2 NPs led to higher variable fluorescence to maximum fluorescence ratio, suggesting that CeO2 NPs enhanced the plant light energy use efficiency by photosystem II. In addition, the presence of CeO2 NPs did not affect Cd accumulation in soybean, but Cd significantly increased the accumulation of Ce in plant tissues, especially in roots and older leaves. The altered Ce in planta distribution was partially associated with the formation of root apoplastic barriers in the co-presence of Cd and CeO2 NPs.

Cerium Oxide Nanoparticles and Bulk Cerium Oxide Leading to Different Physiological and Biochemical Responses in Brassica rapa.

Cerium oxide nanoparticles (CeO2NPs) have been incorporated into many commercial products, and their potential release into the environment through the use and disposal of these products has caused serious concerns. Despite the previous efforts and rapid progress on elucidating the environmental impact of CeO2NPs, the long-term impact of CeO2NPs to plants, a key component of the ecosystem, is still not well understood. The potentially different impact of CeO2NPs and their bulk counterparts to plants is also unclear. The main objectives of this study were (1) to investigate whether continued irrigation with solutions containing different concentrations of CeO2NPs (0, 10, and 100 mg/L) would induce physiological and biochemical adjustments in Brassica rapa in soil growing conditions and (2) to determine whether CeO2NPs and bulk CeO2 particles exert different impacts on plants. The results indicated that bulk CeO2 at 10 and 100 mg/L enhanced plant biomass by 28% and 35%, respectively, while CeO2NPs at equivalent concentrations did not. While the bulk CeO2 treatment resulted in significantly higher concentrations of hydrogen peroxide (H2O2) in plant tissues at the vegetative stage, CeO2NPs led to significantly higher H2O2 levels in plant tissues at the floral stage. The activity of superoxide dismutase (SOD) in Brassica rapa also displayed a growth-stage dependent response to different sizes of CeO2 while catalase (CAT) activity was not affected by either size of CeO2 throughout the life cycle of Brassica rapa. Altogether, the results demonstrated that plant responses to CeO2 exposure varied with the particle sizes and the growth stages of plants.

Single particle ICP-MS method development for the determination of plant uptake and accumulation of CeO2 nanoparticles.

Cerium dioxide nanoparticles (CeO2NPs) are among the most broadly used engineered nanoparticles that will be increasingly released into the environment. Thus, understanding their uptake, transportation, and transformation in plants, especially food crops, is critical because it represents a potential pathway for human consumption. One of the primary challenges for the endeavor is the inadequacy of current analytical methodologies to characterize and quantify the nanomaterial in complex biological samples at environmentally relevant concentrations. Herein, a method was developed using single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) technology to simultaneously detect the size and size distribution of particulate Ce, particle concentration, and dissolved cerium in the shoots of four plant species including cucumber, tomato, soybean, and pumpkin. An enzymatic digestion method with Macerozyme R-10 enzyme previously used for gold nanoparticle extraction from the tomato plant was adapted successfully for CeO2NP extraction from all four plant species. This study is the first to report and demonstrate the presence of dissolved cerium in plant seedling shoots exposed to CeO2NPs hydroponically. The extent of plant uptake and accumulation appears to be dependent on the plant species, requiring further systematic investigation of the mechanisms.

Characterization of gold nanoparticle uptake by tomato plants using enzymatic extraction followed by single-particle inductively coupled plasma-mass spectrometry analysis.

Plant uptake and accumulation of nanoparticles (NPs) represent an important pathway for potential human expose to NPs. Consequently, it is imperative to understand the uptake of accumulation of NPs in plant tissues and their unique physical and chemical properties within plant tissues. Current technologies are limited in revealing the unique characteristics of NPs after they enter plant tissues. An enzymatic digestion method, followed by single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) analysis, was developed for simultaneous determination of gold NP (AuNP) size, size distribution, particle concentration, and dissolved Au concentration in tomato plant tissues. The experimental results showed that Macerozyme R-10 enzyme was capable of extracting AuNPs from tomato plants without causing dissolution or aggregation of AuNPs. The detection limit for quantification of AuNP size was 20 nm, and the AuNP particle concentration detection limit was 1000 NPs/mL. The particle concentration recoveries of spiked AuNPs were high (79-96%) in quality control samples. The developed SP-ICP-MS method was able to accurately measure AuNP size, size distribution, and particle concentration in the plant matrix. The dosing study indicated that tomato can uptake AuNPs as intact particles without alternating the AuNP properties.

Magnetic surfactant-modified clay for enhanced adsorption of mixtures of per- and polyfluoroalkyl substances (PFAS) in snowmelt: Improving practical applicability and efficiency.

The extensive use of per- and polyfluoroalkyl substances (PFAS) in many industrial and consumer contexts, along with their persistent nature and possible health hazards, has led to their recognition as a prevalent environmental issue. While various PFAS removal methods exist, adsorption remains a promising, cost-effective approach. This study evaluated the PFAS adsorption performance of a surfactant-modified clay by comparing it with commercial clay-based adsorbents. Furthermore, the impact of environmental factors, including pH, ionic strength, and natural organic matter, on PFAS adsorption by the modified clay (MC) was evaluated. After proving that the MC was regenerable and reusable, magnetic modified clay (MMC) was synthesized, characterized, and tested for removing a wide range of PFAS in pure water and snowmelt. The MMC was found to have similar adsorption performance as the MC and was able to remove > 90% of the PFAS spiked to the snowmelt. The superior and much better performance of the MMC than powdered activated carbon points to its potential use in removing PFAS from real water matrices at an industrial scale.

Surface Modification of Graphene Oxide for Fast Removal of Per- and Polyfluoroalkyl Substances (PFAS) Mixtures from River Water.

Per- and polyfluoroalkyl substances (PFAS) make up a diverse group of industrially derived organic chemicals that are of significant concern due to their detrimental effects on human health and ecosystems. Although other technologies are available for removing PFAS, adsorption remains a viable and effective method. Accordingly, the current study reported a novel type of graphene oxide (GO)-based adsorbent and tested their removal performance toward removing PFAS from water. Among the eight adsorbents tested, GO modified by a cationic surfactant, cetyltrimethylammonium chloride (CTAC), GO-CTAC was found to be the best, showing an almost 100% removal for all 11 PFAS tested. The adsorption kinetics were best described by the pseudo-second-order model, indicating rapid adsorption. The isotherm data were well supported by the Toth model, suggesting that PFAS adsorption onto GO-CTAC involved complex interactions. Detailed characterization using scanning electron microscopy-energy dispersive X-ray spectroscopy, Fourier transform infrared, thermogravimetric analysis, X-ray diffraction, and X-ray photoelectron spectroscopy confirmed the proposed adsorption mechanisms, including electrostatic and hydrophobic interactions. Interestingly, the performance of GO-CTAC was not influenced by the solution pH, ionic strength, or natural organic matter. Furthermore, the removal efficiency of PFAS at almost 100% in river water demonstrated that GO-CTAC could be a suitable adsorbent for capturing PFAS in real surface water.

A comprehensive trial on PFAS remediation: hemp phytoextraction and PFAS degradation in harvested plants.

Per- and polyfluoroalkyl substances (PFAS) are a class of recalcitrant, highly toxic contaminants, with limited remediation options. Phytoremediation - removal of contaminants using plants - is an inexpensive, community-friendly strategy for reducing PFAS concentrations and exposures. This project is a collaboration between the Mi'kmaq Nation, Upland Grassroots, and researchers at several institutions who conducted phytoremediation field trials using hemp to remove PFAS from soil at the former Loring Air Force base, which has now been returned to the Mi'kmaq Nation. PFAS were analyzed in paired hemp and soil samples using targeted and non-targeted analytical approaches. Additionally, we used hydrothermal liquefaction (HTL) to degrade PFAS in the harvested hemp tissue. We identified 28 PFAS in soil and found hemp uptake of 10 of these PFAS. Consistent with previous studies, hemp exhibited greater bioconcentration for carboxylic acids compared to sulfonic acids, and for shorter-chain compounds compared to longer-chain. In total, approximately 1.4 mg of PFAS was removed from the soil via uptake into hemp stems and leaves, with an approximate maximum of 2% PFAS removed from soil in the most successful area. Degradation of PFAS by HTL was nearly 100% for carboxylic acids, but a portion of sulfonic acids remained. HTL also decreased precursor PFAS and extractable organic fluorine. In conclusion, while hemp phytoremediation does not currently offer a comprehensive solution for PFAS-contaminated soil, this project has effectively reduced PFAS levels at the Loring site and underscores the importance of involving community members in research aimed at remediating their lands.

Albumin-bilirubin score as a predictor of all-cause mortality in patients with hepatitis B virus infection: An analysis of National Health and Nutrition Examination Survey (NHANES) 1999-2018.

Objectives: The Albumin-Bilirubin (ALBI) score has been widely used to assess the prognosis in patients with cirrhosis and hepatocellular carcinoma. This study aimed to analyze the relationship between ALBI score and all-cause mortality in patients with hepatitis B virus (HBV) infection in general. Methods: Patients aged ≥ 18 years with previous or current HBV infection from the National Health and Nutrition Examination Survey (NHANES) in the United States between 1999 and 2018 were enrolled in this retrospective cohort study. Weight univariate and multivariate Cox regression models were used to assess the relationship between ALBI score and all-cause mortality. The area under the receiver operating characteristic curve (AUC) was utilized to assess the predictive effect of ALBI score for all-cause mortality. Results: A total of 3,666 patients were included, of whom 925 (23.53 %) patients died. Compared with ALBI score ≤ -2.6, HBV-infected patients with ALBI score > -2.6 [hazard ratio (HR) = 1.75; 95 % confidence interval (CI): 1.43-2.14] were corrected with a higher all-cause mortality risk after adjusting for confounders. Stratified analyses showed that higher ALBI score was related to a higher risk of all-cause mortality in different patients with HBV infection (All P < 0.05). Furthermore, the ALBI score had good predictive ability for 1-year (AUC = 0.816, 95 %CI: 0.754-0.878), 3-year (AUC = 0.808, 95 %CI: 0.775-0.841), 5-year (AUC = 0.809, 95 %CI: 0.783-0.835), and 10-year (AUC = 0.806, 95 %CI: 0.784-0.827) all-cause mortality. Conclusion: Higher ALBI score was related to a higher risk of all-cause mortality in patients with HBV infection, and the ALBI score showed a good predictive effect for short- and long-term all-cause mortality.

The wide presence of fluorinated compounds in common chemical products and the environment: a review.

The C-F bonds, due to their many unique features, have been incorporated into numerous compounds in countless products and applications. These fluorinated compounds eventually are disposed of and released into the environment through different pathways. In this review, we analyzed the occurrence of these fluorinated compounds in seven types of products (i.e., refrigerants/propellants, aqueous film-forming foam, cosmetics, food packaging, agrochemicals, pharmaceuticals, coating materials) and discussed their fate in the environment. This is followed by describing the quantity of fluorinated compounds from each source based on available data. Total on- and off-site disposal or other releases of 536 fluorinated compounds in 2021 were analyzed using the data sourced from the U.S. EPA Toxics Release Inventory (TRI). Among the chemicals examined, chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) were the primary contributors in terms of total mass. Upon examining the seven sources of fluorinated compounds, it became evident that additional contributors are also responsible for the presence of organofluorine compounds in the environment. Although various toxic degradation products of fluorinated compounds could form in the environment, trifluoroacetic acid (TFA) was specifically highlighted in this review given the fact that it is a common dead-end degradation product of > 1 million chemicals. This paper ended with a discussion of several questions raised from this study. The path forward was elaborated as well for the purpose of protecting the environment and human health.

Effect of surfactant assisted ultrasonic pretreatment on production of volatile fatty acids from mixed food waste.

In this study, the potential effect of surfactant assisted ultrasonic pretreatment on mixed food waste was investigated. Surfactants, such as Rhamnolipid, Sodium dodecyl sulfate; Glucopon and Triton X 100 were evaluated in this work. Among them, the maximum solubilization of chemical oxygen demand of 45.5 % and the highest release of soluble COD of 31 g/L were observed for ultrasonication assisted by Triton X 100 at a dose of 0.01 g/g TS in 30 min. The presence of a surfactant also reduced 27.5 % of energy demand when compared to ultrasonic pretreatment alone. Compared to the non-pretreated samples after anaerobic digestion, ultrasonication assisted by Triton X 100 led to 95 % increase of volatile fatty acid titers and 83 % increase of carbon conversion efficiency. Thus, sonication with the addition of Triton X 100 was proven to be highly effective toward increasing digestibility of and yield of volatile fatty acid from mixed food waste.