Serum SOD1 level predicts the severity and prognosis of community-acquired pneumonia patients.

BACKGROUND: Superoxide dismutase 1 (SOD1) is one of the most important participants of antioxidant enzyme system in biological system. Previous studies have found that SOD1 is associated with many inflammatory diseases. The goal of this study was to assess the associations of serum SOD1 with the severity and prognosis in community-acquired pneumonia (CAP) patients by a prospective cohort study. METHODS: CAP patients were enrolled from the Second Affiliated Hospital of Anhui Medical University. Peripheral blood samples were gathered. The level of serum SOD1 was detected through enzyme linked immunosorbent assay (ELISA). Clinical characteristics and demographic information were analyzed. RESULTS: The level of serum SOD1 was gradually upregulated with elevated CAP severity scores. Spearman correlation coefficient or Pearson rank correlation analyses indicated that serum SOD1 was strongly connected with many clinical parameters among CAP patients. Further linear and logistic regression analyses found that the level of serum SOD1 was positively associated with CRB-65, CURB-65, SMART-COP, and CURXO scores among CAP patients. Moreover, serum higher SOD1 at admission substantially increased the risks of ICU admission, mechanical ventilation, vasoactive agent usage, death, and longer hospital stays during hospitalization. Serum SOD1 level combination with CAP severity scores elevated the predictive abilities for severity and death compared with alone serum SOD1 and CAP severity scores in CAP patients during hospitalization. CONCLUSION: The level of serum SOD1 is positively associated with the severity and poor prognosis in CAP patients, suggesting that SOD1 is implicated in the initiation and progression of CAP. Serum SOD1 may be regarded as a biomarker to appraise the severity and prognosis for CAP patients.

Regulatory Mechanisms of Quorum Sensing System of Bacteria in Response to Chlorine and Ozone Disinfection.

Waterborne pathogens invariably present considerable threats to public health. The quorum sensing (QS) system is instrumental in coordinating bacterial growth and metabolisms. However, the responses and regulatory mechanisms of bacteria to various disinfection technologies through quorum sensing are still unclear. This study examines the inactivation effect of chlorination and ozonation on biofilms and planktonic cells of QS signaling-deficient mutants of Pseudomonas aeruginosa. Cell counting and viability assessment revealed that the combined disinfection of chlorine and ozone was the most effective for inactivating planktonic P. aeruginosa within 10 min of exposure. Additionally, microfluidic chip culture demonstrated that the secretion of quinolone signals escalated biofilms' disinfection resistance. Disinfection exposure significantly altered the gene expression of wild-type strains and QS signaling-deficient mutants. Moreover, the QS system triggered multilayered gene expression programs as a responsive protection to disinfectant exposure, including oxidative stress, ribosome synthesis, and the nutrient absorption of bacteria. These insights broaden our understanding of bacterial QS in response to disinfection, promising potential strategies toward efficient disinfection processes.

Deciphering the formation of granules by n-DAMO and Anammox microorganisms.

Nitrate/nitrite-dependent anaerobic methane oxidation (n-DAMO) process is a promising wastewater treatment technology, but the slow microbial growth rate greatly hinders its practical application. Although high-level nitrogen removal and excellent biomass accumulation have been achieved in n-DAMO granule process, the formation mechanism of n-DAMO granules remains unresolved. To elucidate the role of functional microbes in granulation, this study attempted to cultivate granules dominated by n-DAMO microorganisms and granules coupling n-DAMO with anaerobic ammonium oxidation (Anammox). After long-term operation, dense granules were developed in the two systems where both n-DAMO archaea and n-DAMO bacteria were enriched, whereas granulation did not occur in the other system dominated by n-DAMO bacteria. Extracellular polymeric substances (EPS) measurement indicated the critical role of EPS production in the granulation of n-DAMO process. Metagenomic and metatranscriptomic analyses revealed that n-DAMO archaea and Anammox bacteria were active in EPS biosynthesis, while n-DAMO bacteria were inactive. Consequently, more EPS were produced in the systems containing n-DAMO archaea and Anammox bacteria, leading to the successful development of n-DAMO granules. Furthermore, EPS biosynthesis in n-DAMO systems is potentially regulated by acyl-homoserine lactones and c-di-GMP. These findings not only provide new insights into the mechanism of granule formation in n-DAMO systems, but also hint at potential strategies for management of the granule-based n-DAMO process.

Anaerobic ammonium oxidation coupled with sulfate reduction links nitrogen with sulfur cycle.

Sulfate-dependent ammonium oxidation (Sulfammox) is a critical process linking nitrogen and sulfur cycles. However, the metabolic pathway of microbes driven Sulfammox is still in suspense. The study demonstrated that ammonium was not consumed with sulfate as the sole electron acceptor during long-term enrichment, probably due to inhibition from sulfide accumulation, while ammonium was removed at âˆ¼ 10 mg N/L/d with sulfate and nitrate as electron acceptors. Ammonium and sulfate were converted into nitrogen gas, sulfide, and elemental sulfur. Sulfammox was mainly performed by Candidatus Brocadia sapporoensis and Candidatus Brocadia fulgida, both of which encoded ammonium oxidation pathway and dissimilatory sulfate reduction pathway. Not sulfide-driven autotrophic denitrifiers but Candidatus Kuenenia stuttgartiensis converted nitrate to nitrite with sulfide. The results of this study reveal the specialized metabolism of Sulfammox bacteria (Candidatus Brocadia sapporoensis and Candidatus Brocadia fulgida) and provide insight into microbial relationships during the nitrogen and sulfur cycles.

Nitrate-dependent anaerobic methane oxidation coupled to Fe(III) reduction as a source of ammonium and nitrous oxide.

'Candidatus Methanoperedens nitroreducens' is an archaeal methanotroph with global importance that links carbon and nitrogen cycles and great potential for sustainable operation of wastewater treatment. It has been reported to mediate the anaerobic oxidation of methane through a reverse methanogenesis pathway while reducing nitrate to nitrite. Here, we demonstrate that 'Ca. M. nitroreducens' reduces ferric iron forming ammonium (23.1 %) and nitrous oxide (N2O, 46.5 %) from nitrate. These results are supported with the upregulation of genes coding for proteins responsible for dissimilatory nitrate reduction to ammonium (nrfA), N2O formation (norV, cyt P460), and multiple multiheme c-type cytochromes for ferric iron reduction. Concomitantly, an increase in the N2O-reducing SJA-28 lineage and a decrease in the nitrite-reducing 'Candidatus Methylomirabilis oxyfera' are consistent with the changes in 'Ca. M. nitroreducens' end products. These findings demonstrate the highly flexible physiology of 'Ca. M. nitroreducens' in anaerobic ecosystems with diverse electron acceptor conditions, and further reveals its roles in linking methane oxidation to global biogeochemical cycles. 'Ca. M. nitroreducens' could significantly affect the bioavailability of nitrogen sources as well as the emission of greenhouse gas in natural ecosystems and wastewater treatment plants.

Different oxygen affinities of methanotrophs and Comammox Nitrospira inform an electrically induced symbiosis for nitrogen loss.

Aerobic methanotrophs establish a symbiotic association with denitrifiers to facilitate the process of aerobic methane oxidation coupled with denitrification (AME-D). However, the symbiosis has been frequently observed in hypoxic conditions continuing to pose an enigma. The present study has firstly characterized an electrically induced symbiosis primarily governed by Methylosarcina and Hyphomicrobium for the AME-D process in a hypoxic niche caused by Comammox Nitrospira. The kinetic analysis revealed that Comammox Nitrospira exhibited a higher apparent oxygen affinity compared to Methylosarcina. While the coexistence of comammox and AME-D resulted in an increase in methane oxidation and nitrogen loss rates, from 0.82 ± 0.10 to 1.72 ± 0.09 mmol CH4 d-1 and from 0.59 ± 0.04 to 1.30 ± 0.15 mmol N2 d-1, respectively. Furthermore, the constructed microbial fuel cells demonstrated a pronounced dependence of the biocurrents on AME-D due to oxygen competition, suggesting the involvement of direct interspecies electron transfer in the AME-D process under hypoxic conditions. Metagenomic and metatranscriptomic analysis revealed that Methylosarcina efficiently oxidized methane to formaldehyde, subsequently generating abundant NAD(P)H for nitrate reduction by Hyphomicrobium through the dissimilatory RuMP pathway, leading to CO2 production. This study challenges the conventional understanding of survival mechanism employed by AME-D symbionts, thereby contributing to the characterization responsible for limiting methane emissions and promoting nitrogen removal in hypoxic regions.

4 mC site recognition algorithm based on pruned pre-trained DNABert-Pruning model and fused artificial feature encoding.

DNA 4 mC plays a crucial role in the genetic expression process of organisms. However, existing deep learning algorithms have shortcomings in the ability to represent DNA sequence features. In this paper, we propose a 4 mC site identification algorithm, DNABert-4mC, based on a fusion of the pruned pre-training DNABert-Pruning model and artificial feature encoding to identify 4 mC sites. The algorithm prunes and compresses the DNABert model, resulting in the pruned pre-training model DNABert-Pruning. This model reduces the number of parameters and removes redundancy from output features, yielding more precise feature representations while upholding accuracy.Simultaneously, the algorithm constructs an artificial feature encoding module to assist the DNABert-Pruning model in feature representation, effectively supplementing the information that is missing from the pre-trained features. The algorithm also introduces the AFF-4mC fusion strategy, which combines artificial feature encoding with the DNABert-Pruning model, to improve the feature representation capability of DNA sequences in multi-semantic spaces and better extract 4 mC sites and the distribution of nucleotide importance within the sequence. In experiments on six independent test sets, the DNABert-4mC algorithm achieved an average AUC value of 93.81%, outperforming seven other advanced algorithms with improvements of 2.05%, 5.02%, 11.32%, 5.90%, 12.02%, 2.42% and 2.34%, respectively.

Deep insights into the biofilm formation mechanism and nitrogen-transformation network in a nitrate-dependent anaerobic methane oxidation biofilm.

Nitrate/nitrite-dependent anaerobic methane oxidation (n-DAMO) process offers a promising solution for simultaneously achieving methane emissions reduction and efficient nitrogen removal in wastewater treatment. Although nitrogen removal at a practical rate has been achieved by n-DAMO biofilm process, the mechanisms of biofilm formation and nitrogen transformation remain to be elucidated. In this study, n-DAMO biofilms were successfully developed in the membrane aerated moving bed biofilm reactor (MAMBBR) and removed nitrate at a rate of 159 mg NO3--N L-1 d-1. The obvious increase in the content of extracellular polymeric substances (EPS) indicated that EPS production was important for biofilm development. n-DAMO microorganisms dominated the microbial community, and n-DAMO bacteria were the most abundant microorganisms. However, the expression of biosynthesis genes for proteins and polysaccharides encoded by n-DAMO archaea was significantly more active compared to other microorganisms, suggesting the central role of n-DAMO archaea in EPS production and biofilm formation. In addition to nitrate reduction, n-DAMO archaea were revealed to actively express dissimilatory nitrate reduction to ammonium and nitrogen fixation. The produced ammonium was putatively converted to dinitrogen gas through the joint function of n-DAMO archaea and n-DAMO bacteria. This study revealed the biofilm formation mechanism and nitrogen-transformation network in n-DAMO biofilm systems, shedding new light on promoting the application of n-DAMO process.

On the Number of Linear Regions of Convolutional Neural Networks With Piecewise Linear Activations.

One fundamental problem in deep learning is understanding the excellent performance of deep Neural Networks (NNs) in practice. An explanation for the superiority of NNs is that they can realize a large family of complicated functions, i.e., they have powerful expressivity. The expressivity of a Neural Network with Piecewise Linear activations (PLNN) can be quantified by the maximal number of linear regions it can separate its input space into. In this paper, we provide several mathematical results needed for studying the linear regions of Convolutional Neural Networks with Piecewise Linear activations (PLCNNs), and use them to derive the maximal and average numbers of linear regions for one-layer PLCNNs. Furthermore, we obtain upper and lower bounds for the number of linear regions of multi-layer PLCNNs. Our results suggest that deeper PLCNNs have more powerful expressivity than shallow PLCNNs, while PLCNNs have more expressivity than fully-connected PLNNs per parameter, in terms of the number of linear regions.

High Engraftment and Metastatic Rates in Orthotopic Xenograft Models of Gastric Cancer via Direct Implantation of Tumor Cell Suspensions.

Although the implantation of intact tumor fragments is a common practice to generate orthotopic xenografts to study tumor invasion and metastasis, the direct implantation of tumor cell suspensions is necessary when prior manipulations of tumor cells are required. However, the establishment of orthotopic xenografts using tumor cell suspensions is not mature, and a comparative study directly comparing their engraftment and metastatic capabilities is lacking. It is unclear whether tumor fragments are superior to cell suspensions for successful engraftment and metastasis. In this study, we employed three GC cell lines with varying metastatic capacities to stably express firefly luciferase for monitoring tumor progression in real time. We successfully minimized the risk of cell leakage during the orthotopic injection of tumor cell suspensions without Corning Matrigel by systematically optimizing the surgical procedure, injection volume, and needle size options. Comparable high engraftment and metastatic rates between these two methods were demonstrated using MKN-45 cells with a strong metastatic ability. Importantly, our approach can adjust the rate of tumor progression flexibly and cuts the experimental timeline from 10-12 weeks (for tumor fragments) to 4-5 weeks. Collectively, we provided a highly reproducible procedure with a shortened experimental timeline and low cost for establishing orthotopic GC xenografts via the direct implantation of tumor cell suspensions.

Deficiency of FRMD5 results in neurodevelopmental dysfunction and autistic-like behavior in mice.

The pathophysiology of autism spectrum disorders (ASDs) is causally linked to postsynaptic scaffolding proteins, as evidenced by numerous large-scale genomic studies [1, 2] and in vitro and in vivo neurobiological studies of mutations in animal models [3, 4]. However, due to the distinct phenotypic and genetic heterogeneity observed in ASD patients, individual mutation genes account for only a small proportion (<2%) of cases [1, 5]. Recently, a human genetic study revealed a correlation between de novo variants in FERM domain-containing-5 (FRMD5) and neurodevelopmental abnormalities [6]. In this study, we demonstrate that deficiency of the scaffolding protein FRMD5 leads to neurodevelopmental dysfunction and ASD-like behavior in mice. FRMD5 deficiency results in morphological abnormalities in neurons and synaptic dysfunction in mice. Frmd5-deficient mice display learning and memory dysfunction, impaired social function, and increased repetitive stereotyped behavior. Mechanistically, tandem mass tag (TMT)-labeled quantitative proteomics revealed that FRMD5 deletion affects the distribution of synaptic proteins involved in the pathological process of ASD. Collectively, our findings delineate the critical role of FRMD5 in neurodevelopment and ASD pathophysiology, suggesting potential therapeutic implications for the treatment of ASD.

Prediction of miRNA-disease associations based on strengthened hypergraph convolutional autoencoder.

Most existing graph neural network-based methods for predicting miRNA-disease associations rely on initial association matrices to pass messages, but the sparsity of these matrices greatly limits performance. To address this issue and predict potential associations between miRNAs and diseases, we propose a method called strengthened hypergraph convolutional autoencoder (SHGAE). SHGAE leverages multiple layers of strengthened hypergraph neural networks (SHGNN) to obtain robust node embeddings. Within SHGNN, we design a strengthened hypergraph convolutional network module (SHGCN) that enhances original graph associations and reduces matrix sparsity. Additionally, SHGCN expands node receptive fields by utilizing hyperedge features as intermediaries to obtain high-order neighbor embeddings. To improve performance, we also incorporate attention-based fusion of self-embeddings and SHGCN embeddings. SHGAE predicts potential miRNA-disease associations using a multilayer perceptron as the decoder. Across multiple metrics, SHGAE outperforms other state-of-the-art methods in five-fold cross-validation. Furthermore, we evaluate SHGAE on colon and lung neoplasms cases to demonstrate its ability to predict potential associations. Notably, SHGAE also performs well in the analysis of gastric neoplasms without miRNA associations.

Revisiting the Engineering Roadmap of Nitrate/Nitrite-Dependent Anaerobic Methane Oxidation.

Nitrate/nitrite-dependent anaerobic oxidation of methane (n-DAMO) is a recently discovered process, which provides a sustainable perspective for simultaneous nitrogen removal and greenhouse gas emission (GHG) mitigation by using methane as an electron donor for denitrification. However, the engineering roadmap of the n-DAMO process is still unclear. This work constitutes a state-of-the-art review on the classical and most recently discovered metabolic mechanisms of the n-DAMO process. The versatile combinations of the n-DAMO process with nitrification, nitritation, and partial nitritation for nitrogen removal are also clearly presented and discussed. Additionally, the recent advances in bioreactor development are systematically reviewed and evaluated comprehensively in terms of methane supply, biomass retention, membrane requirement, startup time, reactor performance, and limitations. The key issues including enrichment and operation strategy for the scaling up of n-DAMO-based processes are also critically addressed. Moreover, the challenges inherent to implementing the n-DAMO process in practical applications, including application scenario recognition, GHG emission mitigation, and operation under realistic conditions, are highlighted. Finally, prospects as well as opportunities for future research are proposed. Overall, this review provides a roadmap for potential applications and further development of the n-DAMO process in the field of wastewater treatment.

Evidence for Nitrous Oxide Emissions by Nitrite-Dependent Anaerobic Methane Oxidizing Bacteria.

Nitrite-dependent anaerobic methane oxidizing (n-DAMO) bacteria generally convert nitrite to dinitrogen and bypass the nitrous oxide (N2O) formation step. However, N2O is often detected in n-DAMO bacteria dominated cultures and it remains an open question as to the microbial origin of N2O in these enrichments. Using a stable nitrite consuming microbial community enriched for n-DAMO bacteria, we demonstrated that N2O production was coupled to methane oxidation and the higher initial nitrite concentrations led to increased quantities of N2O being formed. Moreover, continuous exposure of the enrichment culture to about 5 mg of N L-1 nitrite resulted in constant N2O being produced (12.5% of nitrite was reduced to N2O). Metatranscriptomic analyses revealed that nitrite reductase (nirS) and nitric oxide reductase (norZ) transcripts from n-DAMO bacteria increased in response to nitrite exposure. No other bacteria significantly expressed nor genes under these conditions, suggesting n-DAMO bacteria are responsible for N2O being produced. In a 35-day bioreactor experiment, N2O produced by the n-DAMO bacteria accumulated when nitrite was in excess; this was found to be up to 3.2% of the nitrogen that resulted from nitrite removal. Together, these results suggested that excess nitrite is an important driver of N2O production by n-DAMO bacteria. To this end, proper monitoring and control of nitrite levels in wastewater treatment plants would be effective strategies for mitigating N2O emissions to the atmosphere.

Model-based assessment of mainstream nitrate/nitrite-dependent anaerobic methane oxidation and Anammox process in granular sludge at low temperature.

The process of nitrate/nitrite-dependent anaerobic methane oxidation (n-DAMO) coupled with anaerobic ammonium oxidation (Anammox) is one of groundbreaking discoveries for nitrogen removal and methane emission reduction from wastewater simultaneously. Yet its treatment of mainstream wastewater at low temperature is still a major challenge. In this work, a one-dimensional granular sludge model incorporating Arrhenius conversion for temperature effects was constructed to depict the relationships among n-DAMO microorganisms and Anammox. The model framework was successfully evaluated with 380 days measurement data from a membrane granular sludge reactor (MGSR) operated at temperature of 20-10 °C and fed with ammonium and nitrite. The model could satisfactorily predict the kinetics of nitrogen removal rates, effluent nitrogen concentrations and biomass fractions in MGSR at varying temperatures. Despite the decrease in microbial activity of functional microorganisms, the coupled n-DAMO and Anammox process based on granule system in mainstream wastewater treatment achieved a TN removal efficiency of about 98 % and a stable nitrogen removal rate of 0.55 g L-1 d-1. The model developed is expected to facilitate fundamentally understanding the underlying mechanisms of the coupled process and provide proposals for its practical engineering application in wastewater treatment plants.

Deep insights into the population shift of n-DAMO and Anammox in granular sludge: From sidestream to mainstream.

Granular sludge combined n-DAMO and Anammox (n-D/A) is an energy-efficient biotechnique for the simultaneous removal of nitrogen and dissolved methane from wastewater. However, the lack of knowledge so far about the metabolic interactions between n-DAMO and Anammox in response to operation condition in granular sludge restrains the development of this biotechnology. To address this gap, three independent membrane granular sludge reactors (MGSRs) were designed to carry out the granule-based n-D/A process under different conditions. We provided the first deep insights into the metabolic interactions between n-DAMO and Anammox in granular sludge via combined metagenomic and metatranscriptomic analyses. Our study unveiled a clear population shift of n-DAMO community from Candidatus Methanoperedens to Candidatus Methylomirabilis from sidestream to mainstream. Candidatus Methanoperedens with relative abundance of 25.2% played the major role in nitrate reduction and methane oxidation under sidestream condition, indicated by the high expression activities of mcrA and narG. Candidatus Methylomirabilis dominated the microbial community under mainstream condition with relative abundance of 32.1%, supported by the high expression activities of pmoA and hao. Furthermore, a transition of Anammox population from Candidatus Kuenenia to Candidatus Brocadia was also observed from sidestream to mainstream. Candidatus Kuenenia and Candidatus Brocadia jointly contributed to the primary anaerobic ammonium oxidation suggested by the high expression value of hdh and hzs. Candidatus Methylomirabilis was speculated to perform ammonium oxidation mediated by pMMO under mainstream condition. These findings might help to reveal the microbial interactions and ecological niches of n-DAMO and Anammox microorganisms, shedding light on the optimization and management of the granule-based n-D/A system.

LUNCRW: Prediction of potential lncRNA-disease associations based on unbalanced neighborhood constraint random walk.

Accumulating evidence suggests that long non-coding RNAs (lncRNAs) are associated with various complex human diseases. They can serve as disease biomarkers and hold considerable promise for the prevention and treatment of various diseases. The traditional random walk algorithms generally exclude the effect of non-neighboring nodes on random walking. In order to overcome the issue, the neighborhood constraint (NC) approach is proposed in this study for regulating the direction of the random walk by computing the effects of both neighboring nodes and non-neighboring nodes. Then the association matrix is updated by matrix multiplication for minimizing the effect of the false negative data. The heterogeneous lncRNA-disease network is finally analyzed using an unbalanced random walk method for predicting the potential lncRNA-disease associations. The LUNCRW model is therefore developed for predicting potential lncRNA-disease associations. The area under the curve (AUC) values of the LUNCRW model in leave-one-out cross-validation and five-fold cross-validation were 0.951 and 0.9486 ± 0.0011, respectively. Data from published case studies on three diseases, including squamous cell carcinoma, hepatocellular carcinoma, and renal cell carcinoma, confirmed the predictive potential of the LUNCRW model. Altogether, the findings indicated that the performance of the LUNCRW method is superior to that of existing methods in predicting potential lncRNA-disease associations.

Improved sequential production of hydrogen and caproate by addition of biochar prepared from cornstalk residues.

This study proposes a new model in which ethanol and acetate produced by dark fermentation are processed by Clostridium kluyveri for chain elongation to produce caproate with an addition of biochar prepared from cornstalk residues after acid pretreatment and enzymatic hydrolysis (AERBC) in the dark fermentation and chain elongation processes. The results show a 6-25% increase in hydrogen production in dark fermentation with adding AERBC, and the maximum concentration of caproate in the new model reached 1740 mg/L, 61% higher than that in the control group. In addition, caproate was obtained by dark fermentation, using liquid metabolites as substrates with an initial pH range of 6.5-7.5. Finally, the electron balance and electron transfer efficiency in the new model were analyzed, and the role of AERBC in dark fermentation and chain elongation was investigated. This study provides a new reference for the use of dark-fermented liquid metabolites and cornstalk residue.

Thermophilic microorganisms involved in the nitrogen cycle in thermal environments: Advances and prospects.

Thermophilic microorganisms mediated significant element cycles and material conversion in the early Earth as well as mediating current thermal environments. Over the past few years, versatile microbial communities that drive the nitrogen cycle have been identified in thermal environments. Understanding the microbial-mediated nitrogen cycling processes in these thermal environments has important implications for the cultivation and application of thermal environment microorganisms as well as for exploring the global nitrogen cycle. This work provides a comprehensive review of different thermophilic nitrogen-cycling microorganisms and processes, which are described in detail according to several categories, including nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and dissimilatory nitrate reduction to ammonium. In particular, we assess the environmental significance and potential applications of thermophilic nitrogen-cycling microorganisms, and highlight knowledge gaps and future research opportunities.