Qualitative evaluation of connective tissue disease with cytomegalovirus infection: A meta-analysis of case reports.

BACKGROUND: The primary therapies for connective tissue disease include glucocorticoids and immunosuppressants. However, their prolonged usage can precipitate opportunistic infections, such as cytomegalovirus infection. When managing connective tissue disease complicated by cytomegalovirus infection, judicious selection of treatment modalities is crucial. This involves assessing the necessity for antiviral therapy and contemplating the reduction or cessation of glucocorticoids and immunosuppressants. OBJECTIVE: This investigation sought to methodically review existing literature regarding treating connective tissue disease patients with cytomegalovirus infection. METHODS: On July 5, 2023, an exhaustive literature search was conducted. Data analysis utilized the Kruskal-Wallis test or one-way analysis of variance, supplemented by Bonferroni post hoc testing. RESULTS: Our meta-analysis incorporated 88 studies encompassing 146 connective tissue disease patients with CMV infections. The results indicated that patients with connective tissue disease and cytomegalovirus disease benefitted more from antiviral therapy than those not receiving such treatment (P = 0.003, P < 0.005). Furthermore, the strategic reduction of glucocorticoids and/or immunosuppressants was beneficial (P = 0.037, P < 0.05). Poor clinical outcomes with glucocorticoid-immunosuppressant combination therapy compared to other treatment modalities. The findings also suggested that CMV infection patients fare better without Cyclosporine A than using it (P = 0.041, P < 0.05). CONCLUSION: Antiviral therapy is a viable treatment option in cases of connective tissue disease co-occurring with cytomegalovirus disease. Additionally, when connective tissue disease is stable, there is potential merit in reducing glucocorticoids and/or immunosuppressants, especially avoiding the combination of these drugs. For all cytomegalovirus infection patients, Cyclosporine A may be avoided wherever possible for selecting immunosuppressive agents if its use is not deemed essential in the treatment regimen.

Alternative states in microbial communities during artificial aeration: Proof of incubation experiment and development of recurrent neural network models.

Artificial aeration, a widely used method of restoring the aquatic ecological environment by enhancing the re-oxygenation capacity, typically relies upon empirical models to predict ecological dynamics and determine the operating scheme of the aeration equipment. Restoration through artificial aeration is involved in oxic-anoxic transitions, whether these transitions occurred in the form of a regime shift, making the development of predictive models challenging. Here, we confirmed the existence of alternative states in microbial communities during artificial aeration through aeration incubation experiment for the first time and considered its existence in neural network modeling in order to improve model performance. By aeration incubation experiment, it was confirmed that the alternative states exist in microbial communities during artificial aeration by two independent approaches, potential analysis and "enterotyping" approach. Comparing neural network models with and without considering the existence of alternative states, it was found that considering the existence of alternative states in modeling could improve the performance of neural network model. Our study provides a reference for the prediction of systems containing time series data where the current state will have an impact on later states. The developed model could be used for optimizing the operating scheme of the artificial aeration.

Structural basis of the specificity and interaction mechanism of Bmf binding to pro-survival Bcl-2 family proteins.

The apoptotic pathway is regulated by protein-protein interactions between members of the Bcl-2 family. Pro-survival Bcl-2 family proteins act as cell guardians and protect cells against death. Selective binding and neutralization of BH3-only proteins with pro-survival Bcl-2 family proteins is critical for initiating apoptosis. In this study, the binding assay shows that the BH3 peptide derived from the BH3-only protein Bmf has a high affinity for the pro-survival proteins Bcl-2 and Bcl-xL, but a much lower affinity for Mcl-1. The complex structures of Bmf BH3 with Bcl-2, Bcl-xL and Mcl-1 reveal that the α-helical Bmf BH3 accommodates into the canonical groove of these pro-survival proteins, but the conformational changes and some interactions are different among the three complexes. Bmf BH3 forms conserved hydrophobic and salt bridge interactions with Bcl-2 and Bcl-xL, and also establishes several hydrogen bonds to support their binding. However, the highly conserved Asp-Arg salt bridge is not formed in the Mcl-1/Bmf BH3 complex, and few hydrogen bonds are observed. Furthermore, mutational analysis shows that substitutions of less-conserved residues in the α2-α3 region of these pro-survival Bcl-2 family proteins, as well as the highly conserved Arg, lead to significant changes in their binding affinity to Bmf BH3, while substitutions of less-conserved residues in Bmf BH3 have a more dramatic effect on its affinity to Mcl-1. This study provides structural insight into the specificity and interaction mechanism of Bmf BH3 binding to pro-survival Bcl-2 family proteins, and helps guide the design of BH3 mimics targeting pro-survival Bcl-2 family proteins.

Constructing a novel signature and predicting the immune landscape of colon cancer using N6-methylandenosine-related lncRNAs.

Background: Colon cancer (CC) is a prevalent malignant tumor that affects people all around the world. In this study, N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) in 473 colon cancers and 41 adjacent tissues of CC patients from The Cancer Genome Atlas (TCGA) were investigated. Method: The Pearson correlation analysis was conducted to examine the m6A-related lncRNAs, and the univariate Cox regression analysis was performed to screen 38 prognostic m6A-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) regression analysis were carried out on 38 prognostic lncRNAs to develop a 14 m6A-related lncRNAs prognostic signature (m6A-LPS) in CC. The availability of the m6A-LPS was evaluated using the Kaplan-Meier and Receiver Operating Characteristic (ROC) curves. Results: Three m6A modification patterns with significantly different N stages, survival time, and immune landscapes were identified. It has been discovered that the m6A-LPS, which is based on 14 m6A-related lncRNAs (TNFRSF10A-AS1, AC245041.1, AL513550.1, UTAT33, SNHG26, AC092944.1, ITGB1-DT, AL138921.1, AC099850.3, NCBP2-AS1, AL137782.1, AC073896.3, AP006621.2, AC147651.1), may represent a new, promising biomarker with great potential. It was re-evaluated in terms of survival rate, clinical features, tumor infiltration immune cells, biomarkers related to Immune Checkpoint Inhibitors (ICIs), and chemotherapeutic drug efficacy. The m6A-LPS has been revealed to be a novel potential and promising predictor for evaluating the prognosis of CC patients. Conclusion: This study revealed that the risk signature is a promising predictive indicator that may provide more accurate clinical applications in CC therapeutics and enable effective therapy strategies for clinicians.

Structures of p53/BCL-2 complex suggest a mechanism for p53 to antagonize BCL-2 activity.

Mitochondrial apoptosis is strictly controlled by BCL-2 family proteins through a subtle network of protein interactions. The tumor suppressor protein p53 triggers transcription-independent apoptosis through direct interactions with BCL-2 family proteins, but the molecular mechanism is not well understood. In this study, we present three crystal structures of p53-DBD in complex with the anti-apoptotic protein BCL-2 at resolutions of 2.3-2.7 Å. The structures show that two loops of p53-DBD penetrate directly into the BH3-binding pocket of BCL-2. Structure-based mutations at the interface impair the p53/BCL-2 interaction. Specifically, the binding sites for p53 and the pro-apoptotic protein Bax in the BCL-2 pocket are mostly identical. In addition, formation of the p53/BCL-2 complex is negatively correlated with the formation of BCL-2 complexes with pro-apoptotic BCL-2 family members. Defects in the p53/BCL-2 interaction attenuate p53-mediated cell apoptosis. Overall, our study provides a structural basis for the interaction between p53 and BCL-2, and suggests a molecular mechanism by which p53 regulates transcription-independent apoptosis by antagonizing the interaction of BCL-2 with pro-apoptotic BCL-2 family members.

Targeting p53 pathways: mechanisms, structures, and advances in therapy.

The TP53 tumor suppressor is the most frequently altered gene in human cancers, and has been a major focus of oncology research. The p53 protein is a transcription factor that can activate the expression of multiple target genes and plays critical roles in regulating cell cycle, apoptosis, and genomic stability, and is widely regarded as the "guardian of the genome". Accumulating evidence has shown that p53 also regulates cell metabolism, ferroptosis, tumor microenvironment, autophagy and so on, all of which contribute to tumor suppression. Mutations in TP53 not only impair its tumor suppressor function, but also confer oncogenic properties to p53 mutants. Since p53 is mutated and inactivated in most malignant tumors, it has been a very attractive target for developing new anti-cancer drugs. However, until recently, p53 was considered an "undruggable" target and little progress has been made with p53-targeted therapies. Here, we provide a systematic review of the diverse molecular mechanisms of the p53 signaling pathway and how TP53 mutations impact tumor progression. We also discuss key structural features of the p53 protein and its inactivation by oncogenic mutations. In addition, we review the efforts that have been made in p53-targeted therapies, and discuss the challenges that have been encountered in clinical development.

Effects of phonological awareness and morphological awareness on blind students' reading comprehension.

The exploration of blind students' reading skills is needed not only for further understanding their reading development but also for providing targeted suggestions for practical education. This study aims to examine the relations among phonological awareness (PA), homograph awareness (HA), compounding awareness (CA) and reading comprehension (RC), and explore the mediating effect of listening comprehension (LC) in Chinese blind students from elementary school. A total of 148 blind and 302 sighted elementary school students completed assessments of PA, HA, CA, LC and RC. The results found that PA, HA and CA were important variables that predicted Chinese blind and sighted students' RC not only directly but also indirectly through LC, which varied across different grades. The findings suggest that there were many similarities that exist in the influencing mechanism of RC between Chinese blind and sighted students.

Hydrodynamics-driven community coalescence determines ecological assembly processes and shifts bacterial network stability in river bends.

Community coalescence, i.e., the mixing and merging of microbial communities and their surrounding environments, is prevalent in various ecosystems and potentially acts on ecological processes. River bends are distinguished by significant cross-stream velocities and spiral flow. The flow in river bends causes the mixing of microbial communities, thus making the resultant community (after mixing) different from its precursors (before mixing) through ecological processes. However, so far, no studies have explored the effect of community coalescence on ecological processes and network stability under the hydrodynamic processes of river bends. Here, we explored bacterial community assembly and community coalescence in river bends by coupling hydrodynamic profiling, aqueous biogeochemistry, DNA sequencing, and ecological theory. The results showed that the water flow dominated the community coalescence by regulating the movement of suspended sediments. The main ecological process determining the bacterial community compositions in water was the dispersal process, whereas in sediments it was the selection process. Furthermore, the negative cohesion results showed that community coalescence determined the stability of bacterial networks through competition and predation. This study depicted the bacterial community coalescence in river bends and highlighted their associations with network stability, which might provide new insights into bacterial community assembly and coalescence under complex hydrodynamics in the aquatic environment.

Trophic interactions regulate microbial responses to environmental conditions and partially counteract nitrogen transformation potential in urban river bends.

River bends are distinguished by high biodiversity and elevated rates of biogeochemical activities due to complex hydromorphological processes that form diverse geomorphic units, making it challenging to elucidate the impact of trophic interactions on community assembly and biogeochemical processes. Here, we clarify the effect of trophic interactions in determining the assembly of multi-trophic microbial communities and the impact on nitrogen transformation potential by distinguishing the direct and cascading effects of environmental conditions based on 32 samples collected from a typical urban river bends. It was found that both bacterial and micro-eukaryotic communities were determined by homogeneous selection (indicated by ß-nearest taxon index, accounted for 85% and 48.3%, respectively), whereas the dominant environmental factors were different, being sediment particle size (P < 0.05) and nitrogen (P < 0.05), respectively. Both the microbial co-occurrence network and the significant association (P < 0.05) between ß-nearest taxon index and trophic transfer efficiency changes showed that the trophic interactions strongly shaped microbial communities in the urban river bends. The path modeling suggested that environmental conditions resulted in an increase in abundance of multi-trophic microbial communities via direct effects (mean standardized effects = 0.21), but reductions in abundance of bacteria via cascading effects, i.e., trophic interaction (mean standardized effects = -0.1). When considering direct and cascading effects together, environmental conditions in urban river bends were found to enhance the abundance of microbial communities, with decreasing magnitude at the higher trophic level. Analogously, the path modeling also indicated the nitrogen transformation potential enhanced by environmental conditions via direct effects, but partly counteracted by trophic interactions via cascading effects. The obtained results could provide a theoretical basis for the regulation and restoration of urban rivers.

LncRNA DUXAP8 as a prognostic biomarker for various cancers: A meta-analysis and bioinformatics analysis.

Background: Dual homeoboxes A pseudogene 8 (DUXAP8) is a newly discovered long noncoding RNA that has been shown to function as an oncogene in a variety of human malignant cancers. By integrating available data, this meta-analysis sought to determine the relationship between clinical prognosis and DUXAP8 expression levels in diverse malignancies. Materials and methods: A systematic search was performed to identify eligible studies from several electronic databases from their inception to 25 October 2021. Pooled odds ratios and hazard ratios with 95% CI were used to estimate the association between DUXAP8 expression and survival. For survival analysis, the Kaplan-Meier method and COX analysis were used. Furthermore, we utilized Spearman's correlation analysis to explore the correlation between DUXAP8 and tumor mutational burden (TMB), microsatellite instability (MSI), the related genes of mismatch repair (MMR), DNA methyltransferases (DNMTs), and immune checkpoint biomarkers. Results: Our findings indicated that overexpression of DUXAP8 was related to poor overall survival (OS) (HR = 1.63, 95% CI, 1.49-1.77, p < 0.001). In addition, elevated DUXAP8 expression was closely related to poor OS in several cancers in the TCGA database. Moreover, DUXAP8 expression has been associated with TMB, MSI, and MMR in a variety of malignancies. Conclusion: This study revealed that DUXAP8 might serve as a prognostic biomarker and potential therapeutic target for cancer. It can be used to improve cancer diagnosis, discover potential treatment targets, and improve prognosis.

Identification of prognostic genes in the pancreatic adenocarcinoma immune microenvironment by integrated bioinformatics analysis.

PURPOSE: Pancreatic adenocarcinoma (PAAD) is one of the most common causes of death among solid tumors, and its pathogenesis remains to be clarified. This study aims to elucidate the value of immune/stromal-related genes in the prognosis of PAAD through comprehensive bioinformatics analysis based on the immune microenvironment and validated in Chinese pancreatic cancer patients. METHODS: Gene expression profiles of pancreatic cancer patients were obtained from TCGA database. Differentially expressed genes (DEGs) were identified based on the ESTIMATE algorithm. Gene co-expression networks were constructed using WGCNA. In the key module, survival analysis was used to reveal the prognostic value. Subsequently, we performed functional enrichment analysis to construct a protein-protein interaction (PPI) network. The relationship between tumor immune infiltration and hub genes was analyzed by TIMER and CIBERSORT. Finally, it was validated in the GEO database and in tissues of Chinese pancreatic cancer patients. RESULTS: In the TCGA pancreatic cancer cohort, a low immune/stromal score was associated with a good prognosis. After bioinformatic analysis, 57 genes were identified to be significantly associated with pancreatic cancer prognosis. Among them, up-regulation of four genes (COL6A3, PLAU, MMP11 and MMP14) indicated poor prognosis and was associated with multiple immune cell infiltration. IHC results showed that PLAU protein levels from Chinese pancreatic cancer tissues were significantly higher than those from adjacent non-tumor tissues and were also associated with tumor TNM stage and lymph node metastasis. CONCLUSION: In conclusion, this study demonstrates that PLAU may serve as a new diagnostic and therapeutic target, which is highly expressed in Chinese pancreatic cancer tissues and associated with lymph node metastasis.

New insights into nitrogen removal potential in urban river by revealing the importance of microbial community succession on suspended particulate matter.

The importance of suspended particulate matter (SPM) in nitrogen removal from aquatic environments has been acknowledged in recent years by recognizing the role of attached microbes. However, the succession of attached microbes on suspended particles and their role in nitrogen removal under specific surface microenvironment are still unknown. In this study, the causation among characteristics of SPM, composition and diversity of particle-attached microbial communities, and abundances of nitrogen-related genes in urban rivers was firstly quantitatively established by combing spectroscopy, 16 S rRNA amplicon sequencing, absolute gene quantification and supervised integrated machine learning. SPM in urban rivers, coated with organic layers, was mainly composed of silt and clay (87.59-96.87%) with D50 (medium particle size) of 8.636-30.130 µm. In terms of material composition of SPM, primary mineral was quartz and the four most abundant elements were O, Si, C, Al. The principal functional groups on SPM were hydroxyl and amide. Furthermore, samples with low, medium and high levels of ammoxidation potential were classified into three groups, among which significant differences of microbial communities were found. Samples were also separated into three groups with low, medium and high levels of denitrification potential and significant differences occurred among groups. The particle size, content of functional groups and concentration of SPM were identified as the most significant factors related with microbial communities, playing an important role in succession of particle-attached microbes. In addition, the path model revealed the significantly positive effect of organic matter and particle size on the microbial communities and potential nitrogen removal. The content of hydroxyl and temperature were identified as the most effective predicting factors for ammoxidation potential and denitrification potential respectively by Random Forests Regression models, which had good predictive performances for potential of ammoxidation (R2 = 0.71) and denitrification (R2 = 0.61). These results provide a basis for quickly assessing the ability of nitrogen removal in urban rivers.

Predicting bend-induced heterogeneity in sediment microbial communities by integrating bacteria-based index of biotic integrity and supervised learning algorithms.

Prioritizing the relationship between heterogeneity of sediment habitats and river bends is critical when planning and reconstructing urban rivers. However, the exact relationship between ecological heterogeneity and river bends remains ambiguous. Therefore, this research proposed a new approach to quantify and predict bend-induced ecological heterogeneity, incorporating the bacteria-based index of biotic integrity (Ba-IBI), path model, and random forest regression model. The developed Ba-IBI quantified heterogeneity in sediment microbial communities, ranging from low (1.40) to high (3.97). A path model was developed and validated in order to further investigate the relative contributions of environmental factors to the Ba-IBI. The established path model, which was considered acceptable with a CMIN/df = 1.949 < 4, suggested that primary environmental factors affecting the sediment bacterial communities were flow velocity and ammonium concentration in sediment. To further characterize the relationship between environmental factors and the Ba-IBI, a function was constructed using the random forest regression model that predicts the responses of sediment bacterial communities to environmental factors with R2 = 0.6126. The proposed approach and prediction tools will provide knowledge to improve natural channel design and post-project evaluations in river restoration projects.

Determination of the direct and indirect effects of bend on the urban river ecological heterogeneity.

The ecological heterogeneity created by river bends benefits the diversity of microorganisms, which is vital for the pollutant degradation and overall river health. However, quantitative tools capable of determining the interactions among different trophic levels and species are lacking, and research regarding ecological heterogeneity has been limited to a few species. By integrating the multi-species-based index of biotic integrity (Mt-IBI) and the structure equation model (SEM), an interactions-based prediction modeling framework was established. Based on DNA metabarcoding, a multi-species (i.e., bacteria, protozoans, and metazoans) based index of biotic integrity including 309 candidate metrics was developed. After a three-step screening process, eight core metrics were obtained to assess the ecological heterogeneity, quantitatively. The Mt-IBI value, which ranged from 2.08 to 7.17, was calculated as the sum of each single core metric value. The Mt-IBI revealed that the ecological heterogeneity of concave banks was higher than other sites. According to the result of the SEM, D90 was the controlling factor (r = -0.779) of the ecological heterogeneity under the influence of the river bends. The bend-induced redistribution of sediment particle further influenced the concentrations of carbon, nitrogen, and sulphur. The nitrogen group (r = 0.668) also played an essential role in determining the ecological heterogeneity, follow by carbon group (r = 0.455). Furthermore, the alteration of niches would make a difference on the ecological heterogeneity. This multi-species interactions-based prediction modeling framework proposed a novel method to quantify ecological heterogeneity and provided insight into the enhancement of ecological heterogeneity in river bends.

Integrating experiments with system-level biogeochemical modeling to understand nitrogen cycling of reservoir sediments at elevated hydrostatic pressure.

Impoundment of rivers to construct reservoirs for hydropower and irrigation greatly increase the hydrostatic pressure acting on river sediments with potential repercussions for ecosystem-level microbial activity and metabolism. Understanding the functioning and responses of key biogeochemical cycles such as that of nitrogen cycling to shifting hydrostatic pressure is needed to estimate and predict the systemic nutrient dynamics in deep-water reservoirs. We studied the functioning of bacterial communities involved in nitrogen transformation in bioreactors maintained under contrasting hydrostatic pressures (0.5 MPa-3.0 MPa) and complemented the experimental approach with a functional gene-informed biogeochemical model. The model predictions were broadly consistent with observations from the experiment, suggesting that the rates of N2O production decreased while the sediment concentration of nitrite increased significantly with increasing pressure, at least when exceeding 1.0 MPa. Changes in nitrite reduction (nirS) and aerobic ammonia oxidation (amoA) genes abundances were in accordance with the observed changes in N2O production and nitrite levels. Moreover, the model predicted that the higher pressures (P > 1.5 MPa) would intensify the inhibition of N2 production via denitrification and result in an accumulation of ammonia in the sediment along with a decrease in dissolved oxygen. The results imply that increased hydrostatic pressure caused by dam constructions may have a strong effect on microbial nitrogen conversion, and that this may result in lower nitrogen removal.

Targeting MCL-1 in cancer: current status and perspectives.

Myeloid leukemia 1 (MCL-1) is an antiapoptotic protein of the BCL-2 family that prevents apoptosis by binding to the pro-apoptotic BCL-2 proteins. Overexpression of MCL-1 is frequently observed in many tumor types and is closely associated with tumorigenesis, poor prognosis and drug resistance. The central role of MCL-1 in regulating the mitochondrial apoptotic pathway makes it an attractive target for cancer therapy. Significant progress has been made with regard to MCL-1 inhibitors, some of which have entered clinical trials. Here, we discuss the mechanism by which MCL-1 regulates cancer cell apoptosis and review the progress related to MCL-1 small molecule inhibitors and their role in cancer therapy.

Structural insight into the molecular mechanism of p53-mediated mitochondrial apoptosis.

The tumor suppressor p53 is mutated in approximately half of all human cancers. p53 can induce apoptosis through mitochondrial membrane permeabilization by interacting with and antagonizing the anti-apoptotic proteins BCL-xL and BCL-2. However, the mechanisms by which p53 induces mitochondrial apoptosis remain elusive. Here, we report a 2.5 Å crystal structure of human p53/BCL-xL complex. In this structure, two p53 molecules interact as a homodimer, and bind one BCL-xL molecule to form a ternary complex with a 2:1 stoichiometry. Mutations at the p53 dimer interface or p53/BCL-xL interface disrupt p53/BCL-xL interaction and p53-mediated apoptosis. Overall, our current findings of the bona fide structure of p53/BCL-xL complex reveal the molecular basis of the interaction between p53 and BCL-xL, and provide insight into p53-mediated mitochondrial apoptosis.

Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence.

The simulation of nitrogen dynamics in urban channel confluences is essential for the evaluation and improvement of water quality. The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transformation of the associated materials. However, the transport of microorganisms and chemicals within and among different phases, which could be the rate-limiting step for the nitrogen dynamics, are always neglected or oversimplified in omics-based models. Therefore, this study proposes a novel simulation system coupling genomic and hydraulic information to simulate transport and transformation processes and provide predictions of nitrogen dynamics in a confluence. The proposed model was able to capture multiphase mass transport, microbial population dynamics, and nitrogen transformation and accurately predict gene abundances and nitrogen concentrations in both water and sediment; the mean relative errors were all lower than 40%. The model emphasized the importance of transport processes, which contributed more than 90% to gene abundances and chemical concentrations. Moreover, the simulation of reaction rates exhibited the specific nitrogen transformation processes in the confluence. The sulfide oxidation and the nitrate reduction and anaerobic ammonium oxidation, with the participation of the genes nap and hzo, respectively, were promoted as the main processes of nitrate and nitrite reduction.

Bend-induced sediment redistribution regulates deterministic processes and stimulates microbial nitrogen removal in coarse sediment regions of river.

Understanding the differences of biogeochemical processes between straight and bent channel is important for weighting them in urban river planning and reconstruction. Shifts in the assembly of the sediment microbial community of bent channels are key, but understudied, component of bend-induced increases in biogeochemical reaction rates. Here, the assembly of microbial community and its feedback to nitrogen transformation in urban river bends were firstly studied by coupling ecological theory, aqueous biogeochemistry, DNA sequencing, and hydrodynamic profiling. It was found that the sediment particle size was the main driving force for producing the significant difference of microbial community structure in river bends. Homogeneous selection, quantified by ß-nearest taxon index (ßNTI), emerged in the urban river bends and accounted for 79.2% of all ecological processes. Moreover, a significant positive relationship between ßNTI and the sediment particle size indicated that shifts in particle size were associated with shifts in deterministic selective pressures, which govern the composition of the microbial community. The significant correlation between the ßNTI and changes in nitrate concentration also indicated that nitrate leads to deterministic processes, which select microbial taxa. These microbial taxa which are governed by deterministic processes show specific nitrogen transformation traits, and react on the nitrate concentration. A multiphase transport model allowed the separation of the effects of deterministic processes on nitrogen concentration from measured concentration influenced by complex biogeochemical processes. The results indicated that both the ammonia transformation and microbial nitrogen removal were stimulated in coarse sediment regions of the river bends, and were confirmed by abundant differences of microbial taxa that could promote ammoxidation and denitrification. The coarse sediment benefits microbial nitrogen removal in urban river bends, a discovery that should inform urban river reconstruction designs and the efforts to assess the environmental water capacity of urban rivers.

New Insights into Sediment Transport in Interconnected River-Lake Systems Through Tracing Microorganisms.

A growing awareness of the wider environmental significance of diffuse sediment pollution in interconnected river-lake systems has generated the need for reliable provenance information. Owing to their insufficient ability to distinguish between multiple sources, common sediment source apportionment methods would rarely be a practical solution. On the basis of the inseparable relationships between sediment and adsorbed microorganisms, community-based microbial source tracking may be a novel method of identifying dominant sediment sources in the era of high-throughput sequencing. Dongting Lake was selected as a study area as it receives considerable sediment import from its inflowing rivers during the flood season. This study was conducted to characterize the bacterial community composition of sediment samples from the inflow-river estuaries and quantify their sediment microbe contributions to the central lake. Metagenomic analysis revealed that the community compositions of source sediment samples were significantly different, allowing specific sources to be identified with the machine learning classification program SourceTracker. A modified analysis using SourceTracker found that the major contributors to three major lake districts were the Songzi, Zishui, and Xinqiang Rivers. The impacts of hydrodynamic conditions on source apportionment were further verified and suggested the practicability of this method to offer a systematic and comprehensive understanding of sediment sources, pathways, and transport dynamics. Finally, a novel framework for sediment source-tracking was established to develop effective sediment management and control strategies in river-lake systems.