Chemical Dynamics of Selenium Nanoparticles in Archaeal Systems.

Methanogenic archaea, characterized by their cell membrane lipid molecules consisting of isoprenoid chains linked to glycerol-1-phosphate via ether bonds, exhibit exceptional adaptability to extreme environments. However, this distinct lipid architecture also complicates the interactions between methanogenic archaea and nanoparticles. This study addresses this challenge by exploring the interaction and transformation of selenium nanoparticles (SeNPs) within archaeal Methanosarcina acetivorans C2A. We demonstrated that the effects of SeNPs are highly concentration-dependent, with chemical stimulation of cellular processes at lower SeNPs concentrations as well as oxidative stress and metabolic disruption at higher concentrations. Notably, we observed the formation of a protein corona on SeNPs, characterized by the selective adsorption of enzymes critical for methylotrophic methanogenesis and those involved in selenium methylation, suggesting potential alterations in protein function and metabolic pathways. Furthermore, the intracellular transformation of SeNPs into both inorganic and organic selenium species highlighted their bioavailability and dynamic transformation within archaea. These findings provide vital insights into the nano-bio interface in archaeal systems, contributing to our understanding of archaeal catalysis and its broader applications.

Nitrogen Forms Regulate the Response of Microcystis aeruginosa to Nanoplastics at Environmentally Relevant Nitrogen Concentrations.

As essential primary producers, cyanobacteria play a major role in global carbon and nitrogen cycles. Though the influence of nanoplastics on the carbon metabolism of cyanobacteria is well-studied, little is known about how nanoplastics affect their nitrogen metabolism, especially under environmentally relevant nitrogen concentrations. Here, we show that nitrogen forms regulated growth inhibition, nitrogen consumption, and the synthesis and release of microcystin (MC) in Microcystis aeruginosa exposed to 10 µg/mL amino-modified polystyrene nanoplastics (PS-NH2) with a particle size of 50 nm under environmentally relevant nitrogen concentrations of nitrate, ammonium, and urea. We demonstrate that PS-NH2 inhibit M. aeruginosa differently in nitrate, urea, and ammonium, with inhibition rates of 51.87, 39.70, and 36.69%, respectively. It is caused through the differences in impairing cell membrane integrity, disrupting redox homeostasis, and varying nitrogen transport pathways under different nitrogen forms. M. aeruginosa respond to exposure of PS-NH2 by utilizing additional nitrogen to boost the production of amino acids, thereby enhancing the synthesis of MC, extracellular polymeric substances, and membrane phospholipids. Our results found that the threat of nanoplastics on primary producers can be regulated by the nitrogen forms in freshwater ecosystems, contributing to a better understanding of nanoplastic risks under environmentally relevant conditions.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

OBJECTIVE: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). METHODS: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). RESULTS: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. CONCLUSION: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

Christensenella minuta interacts with multiple gut bacteria.

Introduction: Gut microbes form complex networks that significantly influence host health and disease treatment. Interventions with the probiotic bacteria on the gut microbiota have been demonstrated to improve host well-being. As a representative of next-generation probiotics, Christensenella minuta (C. minuta) plays a critical role in regulating energy balance and metabolic homeostasis in human bodies, showing potential in treating metabolic disorders and reducing inflammation. However, interactions of C. minuta with the members of the networked gut microbiota have rarely been explored. Methods: In this study, we investigated the impact of C. minuta on fecal microbiota via metagenomic sequencing, focusing on retrieving bacterial strains and coculture assays of C. minuta with associated microbial partners. Results: Our results showed that C. minuta intervention significantly reduced the diversity of fecal microorganisms, but specifically enhanced some groups of bacteria, such as Lactobacillaceae. C. minuta selectively enriched bacterial pathways that compensated for its metabolic defects on vitamin B1, B12, serine, and glutamate synthesis. Meanwhile, C. minuta cross-feeds Faecalibacterium prausnitzii and other bacteria via the production of arginine, branched-chain amino acids, fumaric acids and short-chain fatty acids (SCFAs), such as acetic. Both metagenomic data analysis and culture experiments revealed that C. minuta negatively correlated with Klebsiella pneumoniae and 14 other bacterial taxa, while positively correlated with F. prausnitzii. Our results advance our comprehension of C. minuta's in modulating the gut microbial network. Conclusions: C. minuta disrupts the composition of the fecal microbiota. This disturbance is manifested through cross-feeding, nutritional competition, and supplementation of its own metabolic deficiencies, resulting in the specific enrichment or inhibition of the growth of certain bacteria. This study will shed light on the application of C. minuta as a probiotic for effective interventions on gut microbiomes and improvement of host health.

A hybrid photocatalytic system enables direct glucose utilization for methanogenesis.

Integration of methanogenic archaea with photocatalysts presents a sustainable solution for solar-driven methanogenesis. However, maximizing CH4 conversion efficiency remains challenging due to the intrinsic energy conservation and strictly restricted substrates of methanogenic archaea. Here, we report a solar-driven biotic-abiotic hybrid (biohybrid) system by incorporating cadmium sulfide (CdS) nanoparticles with a rationally designed methanogenic archaeon Methanosarcina acetivorans C2A, in which the glucose synergist protein and glucose kinase, an energy-efficient route for glucose transport and phosphorylation from Zymomonas mobilis, were implemented to facilitate nonnative substrate glucose for methanogenesis. We demonstrate that the photo-excited electrons facilitate membrane-bound electron transport chain, thereby augmenting the Na+ and H+ ion gradients across membrane to enhance adenosine triphosphate (ATP) synthesis. Additionally, this biohybrid system promotes the metabolism of pyruvate to acetyl coenzyme A (AcCoA) and inhibits the flow of AcCoA to the tricarboxylic acid (TCA) cycle, resulting in a 1.26-fold augmentation in CH4 production from glucose-derived carbon. Our results provide a unique strategy for enhancing methanogenesis through rational biohybrid design and reprogramming, which gives a promising avenue for sustainably manufacturing value-added chemicals.

A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features.

OBJECTIVE: This study aims to develop and validate an innovative radiopathomics model that combines radiomics and pathomics features to effectively differentiate between stages I-II and stage III gastric cancer (pathological staging). METHODS: Our study included 200 patients with well-defined stages of gastric cancer divided into a training cohort (n = 140) and a test cohort (n = 60). Radiomics features were extracted from contrast-enhanced CT images using PyRadiomics, while pathomics features were obtained from whole slide images of pathological specimens through a fine-tuned deep learning model (ResNet-18). After rigorous feature dimensionality reduction and selection, we constructed radiomics models (SVM_rad, LR_rad, and MLP_rad) and pathomics models (SVM_path, LR_path, and MLP_path) utilizing support vector machine (SVM), logistic regression (LR), and multilayer perceptron (MLP) algorithms. The optimal radiomics and pathomics models were chosen based on comprehensive evaluation criteria such as ROC curves, Hosmer‒Lemeshow tests, and calibration curve tests. Feature patterns extracted from the best-performing radiomics model (MLP_rad) and pathomics model (SVM_rad) were integrated to create a powerful radiopathomics nomogram. RESULTS: From a pool of 1834 radiomics features extracted from CT images, 14 were selected to construct radiomics models. Among these, the MLP_rad model exhibited the most robust predictive performance (AUC, training cohort: 0.843; test cohort: 0.797). Likewise, 10 pathomics features were chosen from 512 extracted from whole slide images to build pathomics models, with the SVM_path model demonstrating the highest predictive efficiency (AUC, training cohort: 0.937; test cohort: 0.792). The combined radiopathomics nomogram model exhibited optimal discriminative ability (AUC, training cohort: 0.951; test cohort: 0.837), as confirmed by decision curve analysis (DCA), which indicated superior clinical effectiveness. CONCLUSION: This study presents a cutting-edge radiopathomics nomogram model designed to predict pathological staging in gastric cancer, distinguishing between stages I-II and stage III. Our research leverages preoperative CT images and histopathological slides to forecast gastric cancer staging accurately, potentially facilitating the estimation of staging before radical gastric cancer surgery in the future.

Predicting MYCN amplification in paediatric neuroblastoma: development and validation of a 18F-FDG PET/CT-based radiomics signature.

OBJECTIVES: To develop and validate an 18F-FDG PET/CT-based clinical-radiological-radiomics nomogram and evaluate its value in the diagnosis of MYCN amplification (MNA) in paediatric neuroblastoma (NB) patients. METHODS: A total of 104 patients with NB were retrospectively included. We constructed a nomogram to predict MNA based on radiomics signatures, clinical and radiological features. The multivariable logistic regression and the least absolute shrinkage and selection operator (LASSO) were used for feature selection. Radiomics models are constructed using decision trees (DT), logistic regression (LR) and support vector machine (SVM) classifiers. A clinical-radiological (C-R) model was developed using clinical and radiological features. A clinical-radiological-radiomics (C-R-R) model was developed using the C-R model of the best radiomics model. The prediction performance was verified by receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA) in the training and validation cohorts. RESULTS: The present study showed that four radiomics signatures were significantly correlated with MNA. The SVM classifier was the best model of radiomics signature. The C-R-R model has the best discriminant ability to predict MNA, with AUCs of 0.860 (95% CI, 0.757-0.963) and 0.824 (95% CI, 0.657-0.992) in the training and validation cohorts, respectively. The calibration curve indicated that the C-R-R model has the goodness of fit and DCA confirms its clinical utility. CONCLUSION: Our research provides a non-invasive C-R-R model, which combines the radiomics signatures and clinical and radiological features based on 18F-FDGPET/CT images, shows excellent diagnostic performance in predicting MNA, and can provide useful biological information with stratified therapy. CRITICAL RELEVANCE STATEMENT: Radiomic signatures of 18F-FDG-based PET/CT can predict MYCN amplification in neuroblastoma. KEY POINTS: • Radiomic signatures of 18F-FDG-based PET/CT can predict MYCN amplification in neuroblastoma. • SF, LDH, necrosis and TLG are the independent risk factors of MYCN amplification. • Clinical-radiological-radiomics model improved the predictive performance of MYCN amplification.

High Emission Efficiency and Thermal Stability in Zero-Dimensional Hybrid Zinc Halide as a Blue Light Emitter.

Exploring highly efficient blue-emissive lead-free halide materials is a significant and challenging objective in the study of luminescent materials. This study reports the synthesis of a new zero-dimensional (0D) hybrid zinc halide of [CYP]ZnBr4 (CYP = 1-cyclohexylpiperazine) containing an isolated [ZnBr4]2- tetrahedron. [CYP]ZnBr4 exhibits strong blue light emission with a high photoluminescence quantum yield (PLQY) of 79.22%, surpassing all previously reported 0D zinc halide counterparts. According to the theoretical and experimental studies, the blue light emission is attributed to intrinsic self-trapped excitons resulting from strong electron-phonon coupling and structural deformation. Importantly, [CYP]ZnBr4 demonstrates excellent structural and luminescence stability toward high temperatures (180 °C) over at least half a month. High luminescence efficiency and stability enable [CYP]ZnBr4 to be an efficient blue phosphor to fabricate white light-emitting diodes (LEDs), which produces high-quality white light with a color rendering index (CRI) of 93.1 and a correlated color temperature (CCT) of 5304 K, closely resembling natural sunlight. This white LED also exhibits consistent performance and stability across different drive currents, suggesting the potential for high-power optoelectronic applications. Overall, this study paves the way for the utilization of 0D hybrid halides in advanced solid-state lighting applications.

Incorporation of Selenium Derived from Nanoparticles into Plant Proteins in Vivo.

Diets comprising selenium-deficient crops have been linked to immune disorders and cardiomyopathy. Selenium nanoparticles (SeNPs) have emerged as a promising nanoplatform for selenium-biofortified agriculture. However, SeNPs fail to reach field-scale applications due to a poor understanding of the fundamental principles of its behavior. Here, we describe the transport, transformation, and bioavailability of SeNPs through a combination of in vivo and in vitro experiments. We show synthesized amorphous SeNPs, when sprayed onto the leaves of Arabidopsis thaliana, are rapidly biotransformed into selenium(IV), nonspecifically incorporated as selenomethionine (SeMet), and specifically incorporated into two selenium-binding proteins (SBPs). The SBPs identified were linked to stress and reactive oxygen species (mainly H2O2 and O2-) reduction, processes that enhance plant growth and primary root elongation. Selenium is transported both upwards and downwards in the plant when SeNPs are sprayed onto the leaves. With the application of Silwet L-77 (a common agrochemical surfactant), selenium distributed throughout the whole plant including the roots, where pristine SeNPs cannot reach. Our results demonstrate that foliar application of SeNPs promotes plant growth without causing nanomaterial accumulation, offering an efficient way to obtain selenium-fortified agriculture.

Core-Shell Au@Nanoplastics as a Quantitative Tracer to Investigate the Bioaccumulation of Nanoplastics in Freshwater Ecosystems.

Studies on the adverse effects of nanoplastics (NPs, particle diameter <1000 nm) including physical damage, oxidative stress, impaired cell signaling, altered metabolism, developmental defects, and possible genetic damage have intensified in recent years. However, the analytical detection of NPs is still a bottleneck. To overcome this bottleneck and obtain a reliable and quantitative distribution analysis in complex freshwater ecosystems, an easily applicable NP tracer to simulate their fate and behavior is needed. Here, size- and surface charge-tunable core-shell Au@Nanoplastics (Au@NPs) were synthesized to study the environmental fate of NPs in an artificial freshwater system. The Au core enables the quantitative detection of NPs, while the polystyrene shell exhibits NP properties. The Au@NPs showed excellent resistance to environmental factors (e.g., 1% hydrogen peroxide solution, simulating gastric fluid, acids, and alkalis) and high recovery rates (>80%) from seawater, lake water, sewage, waste sludge, soil, and sediment. Both positively and negatively charged NPs significantly inhibited the growth of duckweed (Lemna minor L.) but had little effect on the growth of cyanobacteria (Microcystis aeruginosa). In addition, the accumulation of positively and negatively charged NPs in cyanobacteria occurred in a concentration-dependent manner, with positively charged NPs more easily taken up by cyanobacteria. In contrast, negatively charged NPs were more readily internalized in duckweed. This study developed a model using a core-shell Au@NP tracer to study the environmental fate and behavior of NPs in various complex environmental systems.

Reversible structural transformations and color-tunable emissions in organic manganese halides.

Herein, we for the first time report a reversible conversion between green-emissive [DMPZ]MnCl4 and red-emissive [DMPZ]4(MnCl6)(MnCl4)2·(H2O)2 (DMPZ = 1,4-dimethylpiperazine) using kinetic and thermodynamic controlling strategies. Significantly, the synchronous structural and emission transformations in single-component organic manganese halides with adjustable emission colors are highlighted.

Developing a Base Editing System for Marine Roseobacter Clade Bacteria.

The Roseobacter clade bacteria are of great significance in marine ecology and biogeochemical cycles, and they are potential microbial chassis for marine synthetic biology due to their versatile metabolic capabilities. Here, we adapted a CRISPR-Cas-based system, base editing, with the combination of nuclease-deactivated Cas9 and deaminase for Roseobacter clade bacteria. Taking the model roseobacter Roseovarius nubinhibens as an example, we achieved precise and efficient genome editing at single-nucleotide resolution without generating double-strand breaks or requesting donor DNAs. Since R. nubinhibens can metabolize aromatic compounds, we interrogated the key genes in the ß-ketoadipate pathway with our base editing system via the introduction of premature STOP codons. The essentiality of these genes was demonstrated, and for the first time, we determined PcaQ as a transcription activator experimentally. This is the first report of CRISPR-Cas-based genome editing in the entire clade of Roseobacter bacteria. We believe that our work provides a paradigm for interrogating marine ecology and biogeochemistry with direct genotype-and-phenotype linkages and potentially opens a new avenue for the synthetic biology of marine Roseobacter bacteria.

Magnetite nanoparticle coating chemistry regulates root uptake pathways and iron chlorosis in plants.

Understanding the fundamental interaction of nanoparticles at plant interfaces is critical for reaching field-scale applications of nanotechnology-enabled plant agriculture, as the processes between nanoparticles and root interfaces such as root compartments and root exudates remain largely unclear. Here, using iron deficiency-induced plant chlorosis as an indicator phenotype, we evaluated the iron transport capacity of Fe3O4 nanoparticles coated with citrate (CA) or polyacrylic acid (PAA) in the plant rhizosphere. Both nanoparticles can be used as a regulator of plant hormones to promote root elongation, but they regulate iron deficiency in plant in distinctive ways. In acidic root exudates secreted by iron-deficient Arabidopsis thaliana, CA-coated particles released fivefold more soluble iron by binding to acidic exudates mainly through hydrogen bonds and van der Waals forces and thus, prevented iron chlorosis more effectively than PAA-coated particles. We demonstrate through roots of mutants and visualization of pH changes that acidification of root exudates primarily originates from root tips and the synergistic mode of nanoparticle uptake and transformation in different root compartments. The nanoparticles entered the roots mainly through the epidermis but were not affected by lateral roots or root hairs. Our results show that magnetic nanoparticles can be a sustainable source of iron for preventing leaf chlorosis and that nanoparticle surface coating regulates this process in distinctive ways. This information also serves as an urgently needed theoretical basis for guiding the application of nanomaterials in agriculture.

Microplastics exhibit accumulation and horizontal transfer of antibiotic resistance genes.

Although the fates of microplastics (0.1-5 mm) in marine environments and freshwater are increasingly studied, little is known about their vector effect in wastewater treatment plants (WWTPs). Previous studies have evaluated the accumulation of antibiotic resistance genes (ARGs) on microplastics, but there is no direct evidence for the selection and horizontal transfer of ARGs on different microplastics in WWTPs. Here, we show biofilm formation as well as bacterial community and ARGs in these biofilms grown on four kinds of microplastics via incubation in the aerobic and anaerobic tanks of a WWTP. Microplastics showed differential capacities for bacteria and ARGs enrichment, differing from those of the culture environment. Furthermore, ARGs in microplastic biofilms were horizontally transferred at frequencies higher than those in water samples in both tanks. Therefore, microplastics in WWTPs can act as substrates for horizontal transfer of ARGs, potentially causing a great harm to the ecological environment and adversely affecting human health.

18F-FDG PET/CT imaging of pediatric peripheral neuroblastic tumor: a combined model to predict the International Neuroblastoma Pathology Classification.

Background: The aim of this study was to evaluate the effect of a model combining a 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT)-based radiomics signature with clinical factors in the preoperative prediction of the International Neuroblastoma Pathology Classification (INPC) type of pediatric peripheral neuroblastic tumor (pNT). Methods: A total of 106 consecutive pediatric pNT patients confirmed by pathology were retrospectively analyzed. Significant features determined by multivariate logistic regression were retained to establish a clinical model (C-model), which included clinical parameters and PET/CT radiographic features. A radiomics model (R-model) was constructed on the basis of PET and CT images. A semiautomatic method was used for segmenting regions of interest. A total of 1,016 radiomics features were extracted. Univariate analysis and the least absolute shrinkage selection operator were then used to select significant features. The C-model was combined with the R-model to establish a combination model (RC-model). The predictive performance was validated by receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA) in both the training cohort and validation cohort. Results: The radiomics signature was constructed using 5 selected radiomics features. The RC-model, which was based on the 5 radiomics features and 3 clinical factors, showed better predictive performance compared with the C-model alone [area under the curve in the validation cohort: 0.908 vs. 0.803; accuracy: 0.903 vs. 0.710; sensitivity: 0.895 vs. 0.789; specificity: 0.917 vs. 0.583; net reclassification improvement (NRI) 0.439, 95% confidence interval (CI): 0.1047-0.773; P=0.01]. The calibration curve showed that the RC-model had goodness of fit, and DCA confirmed its clinical utility. Conclusions: In this preliminary single-center retrospective study, an R-model based on 18F-FDG PET/CT was shown to be promising in predicting INPC type in pediatric pNT, allowing for the noninvasive prediction of INPC and assisting in therapeutic strategies.

Single bubble probe atomic force microscope and impinging-jet technique unravel the interfacial interactions controlled by long chain fatty acid in anaerobic digestion.

Anaerobic digestion of lipid-rich wastewater generally suffers from foaming induced by long chain fatty acid (LCFA). However, a systematic understanding of LCFA inhibition, especially the physical inhibition on interfacial interaction still remains unclear. Here, we combined bubble probe atomic force microscope and impinging-jet technique to unravel the interfacial interactions controlled by long chain fatty acids in anaerobic digestion. We showed that LCFA had a significant inhibition on methane production in anaerobic reactors for the inhibition of the conversion of VFAs to methane. By measuring the LCFA influence on methanogenic archaea Methanosarcina acetivorans C2A, the results demonstrated that methanogenesis was limited for substrates utilization but not metabolic pathways. The impinging-jet technique results indicated that LCFA enhanced bubble separation from anaerobic granules and reduced the bubble-bubble coalescence probability. In addition, the bubble probe atomic force microscope (AFM) revealed that LCFA enhanced the adhesion force between bubbles by enhancing electrical double layer (EDL) repulsion and decreasing hydrophobic interactions. Overall, these results complement framework of LCFA inhibition in anerobic digestion and provide a nanomechanical insight into the fundamental interfacial interactions related to bubbles in anaerobic reactors.

Regulation Effectiveness and Mechanism of Biotransformation Pathway on the Toxicity of Microcystin-LR Target to Protein Phosphatase 2A.

Biotransformation is recognized as a potential pathway to regulate the environmental risk of microcystins (MCs). To explore the regulation effectiveness and mechanism of the biotransformation pathway, six typical MCLR-biotransformation products (MCLR-BTPs) were prepared, and their inhibition effects on protein phosphatase 2A (PP2A) were evaluated. The inhibition effects of the MCLR-BTPs generally decreased with the increase in biothiol molecular weights and polarity, indicating that biotransformation was an effective pathway through which to regulate MCLR toxicity. To further explore the regulation mechanism, the key interaction processes between the MCLR/MCLR-BTPs and the PP2A were explored by homology modeling and molecular docking. The introduced biothiols blocked the covalent binding of Mdha7 to Cys269 but strengthened the hydrogen bond "Mdha7"→Arg268. The changed "Mdha7" intervened the combination of MCLR-BTPs to PP2A by weakening the hydrogen bonds Arg4←Arg214, Arg4→Pro213, Adda5←His118, and Ala1←Arg268, and the ionic bond Glu6-Mn12+. The weakening combination of the MCLR-BTPs to PP2A further attenuated the interactions between the conserved domain and the Mn2+ ions (including the ionic bonds Asp57-Mn12+ and Asp85-Mn12+ and the metal bonds Asp57-Mn12+ and Asn117-Mn12+) and increased the exposure of the Mn2+ ions. Meanwhile, the weakened hydrogen bond Arg4←Arg214 facilitated the combination of the phosphate group to Arg214 (with increased exposure). In this way, the catalytic activity of the PP2A was restored.

Using colloidal AFM probe technique and XDLVO theory to predict the transport of nanoplastics in porous media.

The plastic concentration in terrestrial systems is orders of magnitude higher than that found in marine ecosystems, which has raised global concerns about their potential risk to agricultural sustainability. Previous research on the transport of nanoplastics in soil relied heavily on the qualitative prediction of the mean-field extended Derjaguin-Landau-Verwey-Overbeek theory (XDLVO), but direct and quantitative measurements of the interfacial forces between single nanoplastics and porous media are lacking. In this study, we conducted multiscale investigations ranging from column transport experiments to single particle measurements. The maximum effluent concentration (C/C0) of amino-modified nanoplastics (PS-NH2) was 0.94, whereas that of the carboxyl-modified nanoplastics (PS-COOH) was only 0.33, indicating PS-NH2 were more mobile than PS-COOH at different ionic strengths (1-50 mM) and pH values (5-9). This phenomenon was mainly attributed to the homogeneous aggregation of PS-COOH. In addition, the transport of PS-NH2 in the quartz sand column was inhibited with the increase of ionic strength and pH, and pH was the major factor governing their mobility. The transport of PS-COOH was inhibited with increasing ionic strength and decreasing pH. Hydrophilicity/hydrophobicity-mediated interactions and particle heterogeneity strongly interfered with interfacial forces, leading to the qualitative prediction of XDLVO, contrary to experimental observations. Through the combination of XDLVO and colloidal atomic force microscopy, accurate and quantitative interfacial forces can provide compelling insight into the fate of nanoparticles in the soil environment.

Aged microplastics enhance their interaction with ciprofloxacin and joint toxicity on Escherichia coli.

Microplastics (MPs) in natural environments undergo complex aging processes, changing their interactions with coexisting antibiotics, and posing unpredictable ecological risks. However, the joint toxicity of aged MPs (aMPs) and antibiotics to bacteria, especially at the molecular level, is unclear. In this study, non-thermal plasma technology was used to simultaneously simulate various radical oxidation and physical reactions that occur naturally in the environment, breaking the limitation of simple aging process in laboratory aging technologies. After aging, we investigated the altered properties of aMPs, their interactions with ciprofloxacin (CIP), and the molecular responses of E. coli exposed to pristine MPs (13.5 mg/L), aMPs (13.5 mg/L), and CIP (2 µg/L) individually or simultaneously. aMPs bound far more CIP to their surfaces than pristine MPs, especially in freshwater ecosystems. Notably, the growth of E. coli exposed to aMPs alone was inhibited, whereas pristine MPs exposure didn't affect the growth of E. coli. Moreover, the most differentially expressed genes in E. coli were induced by the coexposure of aMPs and CIP. Although E. coli depended on chemotaxis to improve its flagellar rotation and escaped the stress of pollutants, the coexposure of aMPs and CIP still caused cell membrane damage, oxidative stress, obstruction of DNA replication, and osmotic imbalance in E. coli. This study filled the knowledge gap between the toxicity of aMPs and pristine MPs coexisting with antibiotics at the transcription level, helping in the accurate assessment of the potential risks of MPs to the environment.