Plant trait networks reveal adaptation strategies in the drylands of China.

BACKGROUND: Plants accomplish multiple functions by the interrelationships between functional traits. Clarifying the complex relationships between plant traits would enable us to better understand how plants employ different strategies to adapt to the environment. Although increasing attention is being paid to plant traits, few studies focused on the adaptation to aridity through the relationship among multiple traits. We established plant trait networks (PTNs) to explore the interdependence of sixteen plant traits across drylands. RESULTS: Our results revealed significant differences in PTNs among different plant life-forms and different levels of aridity. Trait relationships for woody plants were weaker, but were more modularized than for herbs. Woody plants were more connected in economic traits, whereas herbs were more connected in structural traits to reduce damage caused by drought. Furthermore, the correlations between traits were tighter with higher edge density in semi-arid than in arid regions, suggesting that resource sharing and trait coordination are more advantageous under low drought conditions. Importantly, our results demonstrated that stem phosphorus concentration (SPC) was a hub trait correlated with other traits across drylands. CONCLUSIONS: The results demonstrate that plants exhibited adaptations to the arid environment by adjusting trait modules through alternative strategies. PTNs provide a new insight into understanding the adaptation strategies of plants to drought stress based on the interdependence among plant functional traits.

Continental-scale niche differentiation of dominant topsoil archaea in drylands.

Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia-oxidizing archaea (AOA) across large-scale environmental gradients remains limited. We hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental-scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental-based processes while the more generalist AOA are assembled mostly via spatial-based processes. Our findings add to existing knowledge of large-scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world.

Insights into the Allosteric Effect of SENP1 Q597A Mutation on the Hydrolytic Reaction of SUMO1 via an Integrated Computational Study.

Small ubiquitin-related modifier (SUMO)-specific protease 1 (SENP1) is a cysteine protease that catalyzes the cleavage of the C-terminus of SUMO1 for the processing of SUMO precursors and deSUMOylation of target proteins. SENP1 is considered to be a promising target for the treatment of hepatocellular carcinoma (HCC) and prostate cancer. SENP1 Gln597 is located at the unstructured loop connecting the helices α4 to α5. The Q597A mutation of SENP1 allosterically disrupts the hydrolytic reaction of SUMO1 through an unknown mechanism. Here, extensive multiple replicates of microsecond molecular dynamics (MD) simulations, coupled with principal component analysis, dynamic cross-correlation analysis, community network analysis, and binding free energy calculations, were performed to elucidate the detailed mechanism. Our MD simulations showed that the Q597A mutation induced marked dynamic conformational changes in SENP1, especially in the unstructured loop connecting the helices α4 to α5 which the mutation site occupies. Moreover, the Q597A mutation caused conformational changes to catalytic Cys603 and His533 at the active site, which might impair the catalytic activity of SENP1 in processing SUMO1. Moreover, binding free energy calculations revealed that the Q597A mutation had a minor effect on the binding affinity of SUMO1 to SENP1. Together, these results may broaden our understanding of the allosteric modulation of the SENP1-SUMO1 complex.

Water content quantitatively affects metabolic rates over the course of plant ontogeny.

Plant metabolism determines the structure and dynamics of ecological systems across many different scales. The metabolic theory of ecology quantitatively predicts the scaling of metabolic rate as a function of body size and temperature. However, the role of tissue water content has been neglected even though hydration significantly affects metabolism, and thus ecosystem structure and functioning. Here, we use a general model based on biochemical kinetics to quantify the combined effects of water content, body size and temperature on plant metabolic rates. The model was tested using a comprehensive dataset from 205 species across 10 orders of magnitude in body size from seeds to mature large trees. We show that water content significantly influences mass-specific metabolic rates as predicted by the model. The scaling exponents of whole-plant metabolic rate vs body size numerically converge onto 1.0 after water content is corrected regardless of body size or ontogenetic stage. The model provides novel insights into how water content together with body size and temperature quantitatively influence plant growth and metabolism, community dynamics and ecosystem energetics.

Activation of liver X receptor suppresses osteopontin expression and ameliorates nephrolithiasis.

Nephrolithiasis is a common disease of the urinary system, of which idiopathic calcium oxalate (CaOx) kidney stones, in particular, are one of the special types. In the initial stages of CaOx kidney stone formation, Randall's plaques (RPs) develop. Liver X receptors (LXRs) inhibit oxidative stress and inflammatory in other diseases; nevertheless, the role of LXRs in nephrolithiasis has yet to be elucidated. In this study, the role of LXRs in the progression of RP formation was investigated. Microarray analysis revealed that LXR/RXR levels were significantly greater in low-plaque tissues (<5%) than in high-plaque tissues (>5%), confirming the link between LXR activation and RP formation. Correspondingly, expression levels of two LXR target genes, LXRα and LXRß, were lower in high-plaque tissues than in low-plaque tissues. In vitro, LXR agonist alleviated calcium oxalate monohydrate-induced cellular calcium deposits and apoptosis. LXR activation decreased reactive oxygen species production and gene expression of inflammatory mediators, including osteopontin that has recently been demonstrated to correlate with the development of RPs. Moreover, p38 MAPK and JNK signaling may mediate LXR-regulated expression in HK-2 cells. In an animal model, the deposition was reduced by activating LXR, and osteopontin expression was also inhibited. Our findings suggest a role for LXRs in the progression of idiopathic CaOx kidney stones; LXR agonists may have therapeutic potential for the treatment of nephrolithiasis.

Models and tests of optimal density and maximal yield for crop plants.

We introduce a theoretical framework that predicts the optimum planting density and maximal yield for an annual crop plant. Two critical parameters determine the trajectory of plant growth and the optimal density, N(opt), where canopies of growing plants just come into contact, and competition: (i) maximal size at maturity, M(max), which differs among varieties due to artificial selection for different usable products; and (ii) intrinsic growth rate, g, which may vary with variety and environmental conditions. The model predicts (i) when planting density is less than N(opt), all plants of a crop mature at the same maximal size, M(max), and biomass yield per area increases linearly with density; and (ii) when planting density is greater than N(opt), size at maturity and yield decrease with -4/3 and -1/3 powers of density, respectively. Field data from China show that most annual crops, regardless of variety and life form, exhibit similar scaling relations, with maximal size at maturity, M(max), accounting for most of the variation in optimal density, maximal yield, and energy use per area. Crops provide elegantly simple empirical model systems to study basic processes that determine the performance of plants in agricultural and less managed ecosystems.

Insights into plant size-density relationships from models and agricultural crops.

There is general agreement that competition for resources results in a tradeoff between plant mass, M, and density, but the mathematical form of the resulting thinning relationship and the mechanisms that generate it are debated. Here, we evaluate two complementary models, one based on the space-filling properties of canopy geometry and the other on the metabolic basis of resource use. For densely packed stands, both models predict that density scales as M(-3/4), energy use as M(0), and total biomass as M(1/4). Compilation and analysis of data from 183 populations of herbaceous crop species, 473 stands of managed tree plantations, and 13 populations of bamboo gave four major results: (i) At low initial planting densities, crops grew at similar rates, did not come into contact, and attained similar mature sizes; (ii) at higher initial densities, crops grew until neighboring plants came into contact, growth ceased as a result of competition for limited resources, and a tradeoff between density and size resulted in critical density scaling as M(-0.78), total resource use as M(-0.02), and total biomass as M(0.22); (iii) these scaling exponents are very close to the predicted values of M(-3/4), M(0), and M(1/4), respectively, and significantly different from the exponents suggested by some earlier studies; and (iv) our data extend previously documented scaling relationships for trees in natural forests to small herbaceous annual crops. These results provide a quantitative, predictive framework with important implications for the basic and applied plant sciences.

Decoupling the dynamic mechanism revealed by FGFR2 mutation-induced population shift.

The fibroblast growth factor receptor 2 (FGFR2) is a key component in cellular signaling networks, and its dysfunctional activation has been implicated in various diseases including cancer and developmental disorders. Mutations at the activation loop (A-loop) have been suggested to trigger an increased basal kinase activity. However, the molecular mechanism underlying this highly dynamic process has not been fully understood due to the limitation of static structural information. Here, we conducted multiple, large-scale Gaussian accelerated molecular dynamics simulations of five (K659E, K659N, K659M, K659Q, and K659T) FGFR2 mutants at the A-loop, and comprehensively analyzed the dynamic molecular basis of FGFR2 activation. The results quantified the population shift of each system, revealing that all mutants had a higher proportion of active-like states. Using Markov state models, we extracted the representative structure of different conformational states and identified key residues related to the increased kinase activity. Furthermore, community network analysis showed enhanced information connections in the mutants, highlighting the long-range allosteric communication between the A-loop and the hinge region. Our findings may provide insights into the dynamic mechanism for FGFR2 dysfunctional activation and allosteric drug discovery.Communicated by Ramaswamy H. Sarma.

Long-neglected contribution of nitrification to N2O emissions in the Yellow River.

Rivers play a significant role in the global nitrous oxide (N2O) budget. However, the microbial sources and sinks of N2O in river systems are not well understood or quantified, resulting in the prolonged neglect of nitrification. This study investigated the isotopic signatures of N2O, thereby quantifying the microbial source of N2O production and the degree of N2O reduction in the Yellow River. Although denitrification has long been considered to be the dominant pathway of N2O production in rivers, our findings indicated that denitrification only accounted for 18.3% (8.2%-43.0%) of the total contribution to N2O production in the Yellow River, with 50.2%-80.2% being concurrently reduced. The denitrification contribution to N2O production (R2 = 0.44, p < 0.01) and N2O reduction degree (R2 = 0.70, p < 0.01) were positively related to the dissolved organic carbon (DOC) content. Similar to urban rivers and eutrophic lakes, denitrification was the primary process responsible for N2O production (43.0%) in certain reaches with high organic content (DOC = 5.29 mg/L). Nevertheless, the denitrification activity was generally constrained by the availability of electron donors (average DOC = 2.51 mg/L) throughout the Yellow River basin. Consequently, nitrification emerged as the primary contributor in the well-oxygenated Yellow River. Additionally, our findings further distinguished the respective contribution of ammonia-oxidizing bacteria (AOB) and archaea (AOA) to N2O emissions. Although AOB dominated the N2O production in the Yellow River, the AOA specie abundance (AOA/(AOA + AOB)) contributed up to 32.6%, which resulted in 25.6% of the total nitrifier-produced N2O, suggesting a significant occurrence of AOA in the oligotrophic Yellow River. Overall, this study provided a non-invasive approach for quantifying the microbial sources and sinks to N2O emissions, and demonstrated the substantial role of nitrification in the large oligotrophic rivers.

Application of nano remediation of mine polluted in acid mine drainage water using machine learning model.

Acid mine drainage (AMD) is the term used to describe drainage from coal mines with high sulfur-bearing rocks. The oxidative weathering of metal sulfides leads to AMD. The acidic environment corrodes more harmful compounds in the soil, which is spread throughout the working area. One such significant metal is copper, which is extracted in massive quantities from ores rich in sulfide. A copper-extraction resin might be created by combining diatomaceous earth (DE) particles with polyethyleneimine (PEI), which is shown to have great selectivity and affinity for copper. In this effort, PEI-DE particles' copper absorption level was examined by using synthetic and actual acid mine drainage samples at varied pH values. The findings of the copper uptake particles have been examined through the Support Vector Machine (SVM) model. Using the n-fold 14 cross-validation approach, the quantities of parameters and C are estimated to be 0.001 and 0.01, respectively. The SVM analysis was correct, and the findings indicated that copper could bind to the material efficiently and preferentially at pH 4. Subsequent water elution studies at a pH value of 1 confirmed the pH-reliant interaction between dissolved Cu and PEI by demonstrating full release of the adsorbed Cu. In this research, the copper absorption of PEI-DE particles from synthetic and genuine AMD specimens was studied based on several pH conditions. The findings suggest that copper may attach to the material effectively and preferentially at pH 4. Studies of filtering water at pH1 later confirmed that all of the adsorbed Cu was released. This shows that the interaction between PEI and dissolved Cu depends on PH.

The allosteric effect of the upper half of SENP1 contributes to its substrate selectivity for SUMO1 over SUMO2.

SUMOylation regulates various cellular process and SENP1 (SUMO-specific protease 1) serves as a SUMO (small ubiquitin-related modifier) specific protease that participates in the SUMO cycle. Given its extensive influences on metabolic activities, SENP1 has gained more and more attentions in clinical treatments. However, there remains a question on why does the SENP1 prefer to process SUMO1 rather than SUMO2. Here, we performed molecular dynamics simulations of SENP1-SUMO1, SENP1-SUMO2, and apo SENP1 systems and observed distinct conformational dynamics in the upper half of the clamp and the three loops in the catalytic center of the SENP1. Principal component analysis revealed that the most prominent canonical variable represented the spatial distribution of the upper half of the clamp, while the openness of the cleft was closely related to the catalytic ability of SENP1. Further analysis of the SENP1-SUMO interactions revealed that the extensive and strong interactions between the SENP1 and SUMO1 were both in the interface of the upper half region and the catalytic center. Dynamic cross-correlation matrix analysis demonstrated that the inter-residue correlations in the SUMO1 system was much stronger, especially in the two essential regions belonging to the upper and lower half of cleft. Based on these observations, we proposed an allosteric propagation model and further testified it using the community analysis. These results revealed the propagation pathway of allosteric communication that contributed to the substrate discrimination of SENP1 upon SUMO1 and SUMO2.Communicated by Ramaswamy H. Sarma.

Estimation of Copper and Cadmium Bioavailability in Contaminated Soil Remediated by Different Plants and Micron Hydroxyapatite.

A three-year in situ remediation experiment was carried out to understand the effect of combined phytoremediation with chemical materials on the bioavailability of heavy metals in soil. Indigenous weed (Setaria pumila), energy plant (Pennisetum sp.), cadmium (Cd)-hyperaccumulator (Sedum plumbizincicola), and copper (Cu)-tolerant plant (Elsholtzia splendens) were used as the phytoremediation plants aided by micron hydroxyapatite (1% wt). The bioavailability of Cu and Cd in soil was evaluated during the three years. The results showed that the four plants combined with micron hydroxyapatite significantly increased soil pH and soil organic carbon (SOC), and decreased Cu and Cd fractions extracted by CaCl2 and diffusive gradients in thin films (DGT) than the untreated soils, respectively. Because of the large biomass, the accumulation of Cu and Cd is the largest in Pennisetum sp. followed by Elsholtzia splendens, Sedum plumbizincicola, and Setaria pumila. The bioavailability of Cu and Cd is significantly negatively correlated with pH, soil organic carbon, available phosphorus, and available potassium. Moreover, the correlation is mainly related to the addition of micron hydroxyapatite. The accumulation of Cu and Cd is the combined action of the soil bioavailability of Cu, Cd, and biomass. Our results suggest that Pennisetum sp. can act as an appropriate remediation plant for phytoremediation aided by amendments.

Construction of a Landscape Design and Greenery Maintenance Scheduling System Based on Multimodal Intelligent Computing and Deep Neural Networks.

Digitalization brings challenges and new opportunities to the development of landscape gardening, "smart gardening," which is a product of landscape gardening in response to the development of the digital era. Based on the multimodal intelligent computing method and deep neural network machine learning algorithm, this paper adopts "digital landscape design logic" to analyze and research smart gardens and digital design. The digital landscape design process and methods are discussed based on design logic, design basis, environment analysis, and results presentation, and the greenery maintenance scheduling system is constructed. The paper focuses on the digital implementation of the environmental analysis of the site and uses Rhino software and Grasshopper visual programming language to build parametric logic, establish parametric analysis models, and conduct a comprehensive analysis of the current environment. The main theme of the whole paper is a logical approach to digital landscape design for smart gardens, using digital technology tools from the perspective of smart garden thinking, combining quantitative analysis and qualitative design, and intervening in digital landscape garden planning and design to explore the application of digital technology and tools.

Isolation of heavy metal-immobilizing and plant growth-promoting bacteria and their potential in reducing Cd and Pb uptake in water spinach.

Heavy metal-immobilizing bacteria are normally capable of stabilizing metals and affecting their absorption by plants. However, few studies have elucidated the mechanisms employed by novel heavy metal-immobilizing and plant growth-promoting bacteria to immobilize Cd and Pb and reduce their uptake by vegetables. In this study, polyamine (PA)-producing strains were isolated and their effects on biomass and metal accumulation in water spinach (Ipomoea aquatica Forssk.) and the underlying mechanisms were investigated. Two PA-producing strains, Enterobacter bugandensis XY1 and Serratia marcescens X43, were isolated. Strains XY1 and X43 reduced the aqueous Cd and Pb levels (49%-52%) under 10 mg L-1 Cd and 20 mg L-1 Pb because of metal ion chelation by bacterially produced PAs and cell adsorption. Further evidence showed that Cd and Pb were bound and precipitated on the bacterial cell surface in the form of Cd(OH)2, CdCO3 and PbO. Compared with strain-free water spinach, greens inoculated with strains XY1 and X43 showed 51%-80% lower Cd and Pb contents. The rhizosphere soil pH and PA contents were significantly higher, and lower contents of the rhizosphere soil acid-soluble fractions of Cd (18%-39%) and Pb (31%-37%) were observed compared to the noninoculated control. Moreover, inoculation with XY1 reduced the diversity of the bacterial community, but the relative abundances of plant growth-promoting and PA-producing bacteria in rhizosphere soil were enriched, which enhanced water spinach resistance to Cd and Pb toxicity. Our findings describe novel heavy metal-immobilizing bacteria that could be used to improve the habitat of vegetables and reduce their uptake of heavy metals.

Remediation of mine polluted soil with nano-enhanced materials: Development of extreme learning machine approaches.

Successful mining soil reclamation promotes ecosystem recovery, reduces negative environmental effects, adds more area for forestry or agricultural purposes, and increases carbon (C) sequestration. In order to increase soil erosion management, improve soil quality, reduce pollutants, and assure safe land application of traditional amendment materials, nanoparticles with exceptionally high deliverability and reactivity may be used as amendments. Iron oxide is being researched for the remediation of industrial soil that is co-contaminated with arsenic (AS) due to the absence of Nano enhanced materials for mine soil reclamation. In order to improve the soil quality of a mine waste that was heavily polluted with As (1807 mg/kg), the effects of iron oxide on the non-specifically and specifically-sorbed As were investigated. Iron oxide was added to the polluted soil at concentrations of 0.5 percent, 2 percent, and 5 percent (w/w). The goal of this work is to define the effect of iron oxide and Zero Valent I nanoparticles (nZVI) in reducing the contamination of soil by the use of soft computing models of extreme learning machines (ELM) with particle swarm optimization (PSO). In this case, the hybrid ELM-PSO has shown good performance as a trustworthy approach after the regression study of RMSE, R-square, and r. The addition of iron oxide dosages decreased the easily accessible As by 92.4 when compared to the untreated soil, with the 5 percent doses having a noticeably greater effect.

Enhancing Mechanisms of the Plant Growth-Promoting Bacterial Strain Brevibacillus sp. SR-9 on Cadmium Enrichment in Sweet Sorghum by Metagenomic and Transcriptomic Analysis.

To explore the mechanism by which the plant growth-promoting bacterium Brevibacillus sp. SR-9 improves sweet sorghum tolerance and enriches soil cadmium (Cd) under pot conditions, the effect of strain SR-9 inoculation on the microbial community of sorghum rhizosphere soil was analyzed by metagenomics. Gene expression in sweet sorghum roots was analyzed using transcriptomics. The results showed that strain SR-9 promoted the growth of sweet sorghum and improved the absorption and enrichment of Cd in the plants. Compared with the uninoculated treatment, the aboveground part and root dry weight in strain SR-9 inoculated with sorghum increased by 21.09% and 17.37%, respectively, and the accumulation of Cd increased by 135% and 53.41%, respectively. High-throughput sequencing showed that strain SR-9 inoculation altered the rhizosphere bacterial community, significantly increasing the relative abundance of Actinobacteria and Firmicutes. Metagenomic analysis showed that after inoculation with strain SR-9, the abundance of genes involved in amino acid transport metabolism, energy generation and conversion, and carbohydrate transport metabolism increased. KEGG functional classification showed that inoculation with strain SR-9 increased the abundance of genes involved in soil microbial metabolic pathways in the rhizosphere soil of sweet sorghum and the activity of soil bacteria. Transcriptome analysis identified 198 upregulated differentially expressed genes in sweet sorghum inoculated with strain SR-9, including those involved in genetic information processing, biological system, metabolism, environmental information processing, cellular process, and human disease. Most of the annotated differentially expressed genes were enriched in the metabolic category and were related to pathways such as signal transduction, carbohydrate metabolism, amino acid metabolism, and biosynthesis of other secondary metabolites. This study showed that plant growth-promoting bacteria can alter the rhizosphere bacterial community composition, increasing the activity of soil bacteria and upregulating gene expression in sweet sorghum roots. The findings enhance our understanding of the microbiological and botanical mechanisms by which plant growth-promoting bacterial inoculation improves the remediation of heavy metals by sorghum.

[High-Throughput Sequencing Combined with Metabonomics to Analyze the Effect of Heavy Metal Contamination on Farmland Soil Microbial Community and Function].

Heavy metal contamination affects microbial composition and diversity. The interaction between heavy metal contamination and soil microorganisms has been a hot topic in ecological research. Battery manufacturing has been going on for over six decades in Xinxiang City, resulting in severe soil heavy metal contamination due to battery wastewater runoff. Few studies have investigated the effect of heavy metal contamination due to long-term battery wastewater runoff on microbial diversity and metabolomics in Xinxiang City. In this study, we collected samples from three heavy metal contaminated sites in Xinxiang City and found that Cd and Pb exceeded the recommended thresholds by 34-66 fold and 1.5-2.32 fold, respectively. High-throughput sequencing showed that Bacillus, Arthrobacter, Sphingomonas, and Streptomyces were the dominant bacteria genera, while Olpidium, Plectosphaerella, and Gibellulopsis were the dominant fungi genera, indicating that heavy metal contaminated soil in Xinxiang City was rich in heavy metal tolerant bacteria and fungi due to the long-term heavy metal stress. Correlation analysis showed that total Cu, DTPA extract Cu, and water soluble Pb were significant factors in bacterial diversity, while total Cd, total Ni, total Pb, total Zn, DTPA extract Cu, and water soluble Pb were significant factors in fungal diversity. To better understand the effect of heavy metal contamination on the metabolism of soil microorganisms, we conducted non-targeted metabolomic profiling, which showed significant differences in metabolites across the samples. Pathway enrichment analysis showed that these differential metabolites were involved in pathways such as metabolism, environmental information processing, and genetic Information Processing, which may play a role in heavy metal stress mitigation and environmental adaptation.

The Seasonal Patterns, Ecological Function and Assembly Processes of Bacterioplankton Communities in the Danjiangkou Reservoir, China.

As the water source for the Middle Route Project of the South-to-North Water Diversion Project (MR-SNWD) of China, the Danjiangkou Reservoir (DJR) is in the process of ecosystem reassembly, but the composition, function, and assembly mechanisms of bacterioplankton communities are not yet clear. In this study, the composition, distribution characteristics and influencing factors of bacterioplankton communities were analyzed by high-throughput sequencing (HTS); PICRUSt2 was used to predict community function; a molecular ecological network was used to analyze bacterioplankton interactions; and the assembly process of bacterioplankton communities was estimated with a neutral model. The results indicated that the communities, function and interaction of bacterioplankton in the DJR had significant annual and seasonal variations and that the seasonal differences were greater than that the annual differences. Excessive nitrogen (N) and phosphorus (P) nutrients in the DJR are the most important factors affecting water quality in the reservoir, N and P nutrients are the main factors affecting bacterial communities. Season is the most important factor affecting bacterioplankton N and P cycle functions. Ecological network analysis indicated that the average clustering coefficient and average connectivity of the spring samples were lower than those of the autumn samples, while the number of modules for the spring samples was higher than that for the autumn samples. The neutral model explained 66.3%, 63.0%, 63.0%, and 70.9% of the bacterioplankton community variations in samples in the spring of 2018, the autumn of 2018, the spring of 2019, and the autumn of 2019, respectively. Stochastic processes dominate bacterioplankton community assembly in the DJR. This study revealed the composition, function, interaction, and assembly of bacterioplankton communities in the DJR, providing a reference for the protection of water quality and the ecological functions of DJR bacterioplankton.

Robotic ureteroplasty with appendiceal onlay flap: an update on the outcomes of 18-month follow-up.

BACKGROUND: To describe our technical experience of robotic appendiceal onlay flap ureteroplasty (RAUP) for complex ureteral stricture disease and report the updated analysis of 18-month follow-up outcomes. METHODS: Since May 2019, nine patients with right ureteral strictures have undergone RAUP in our medical centre. Patients' perioperative data and follow-up information were collected prospectively. Patients were excluded in present study if the postoperative follow-up time was less than 6 months. RESULTS: Eight patients were recruited. Proximal ureteric strictures were present in 5 patients, and 3 patients had middle ureteric strictures. The mean stricture length was 4.3 cm (range, 3.0-6.0 cm). Nephrostomy was performed in 4 patients, and 4 patients had indwelling double-J ureteral stents before they were admitted to our hospital. All operations were implemented successfully without intraoperative complications. The mean operation time was 162 minutes (range, 135-211 minutes), and the mean estimated blood loss was 78 mL (range, 30-200 mL). The mean postoperative hospital stay was 8 days (range, 4-12 days). No patients had high-grade postoperative complications (Clavien-Dindo III and IV) 30 days after surgery. At a mean follow-up of 18 months (range, 6-28 months), all patients were not needed further surgical intervention and could be considered successful. But 2 cases still have stable mild hydronephrosis without symptoms such as flank pain or fever. CONCLUSIONS: RAUP is a workable option for managing long-segment (3-6 cm) proximal and middle ureteral strictures of the right side. The outcomes of 18-month follow-up are satisfactory.

Role of polystyrene microplastics in sunlight-mediated transformation of silver in aquatic environments: Mechanisms, kinetics and toxicity.

Sunlight-oxidative ageing is a common and critical process for microplastics (MPs) in aquatic environments. O2•-, 1O2, and •OH generation has been widely proven in this process, which can alter metal speciation based on its reduction and oxidation potential. Herein, chemical speciation of Ag mediated by polystyrene (PS) MPs was determined under simulated sunlight irradiation. The O2•- generation on the PS MPs surfaces is the vital factor for Ag+ reduction, regardless of acid or base conditions. The 1O2 and •OH are dominant factors, and 1O2 played a more important role than •OH for its higher formation amount, causing oxidative dissolution of newly formed Ag0 nanoparticles (NPs). The Ag NPs can hetero-aggregate with PS MPs through electrostatic interactions with O-containing groups (C-O, C-OH and CO), and co-precipitate from the water phase. This hetero-aggregation can stabilize Ag NPs by inhibiting Ag NPs surface photooxidation and suppressing Ag+ release. Transformation of Ag species (from Ag+ to Ag0 NPs) mediated by sunlight with PS MPs significantly suppressed acute toxicity of Ag+ to Escherichia coli, Selenastrum capricornutum, Daphnia magna and zebrafish. This study emphasized that PS MPs play an important role in the speciation, migration and toxicity of Ag+ in freshwater environments.