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Microbes play a crucial role in human health and disease. Figuring out the relationship between microbes and diseases leads to significant potential applications in disease treatments. It is an urgent need to devise robust and effective computational methods for identifying disease-related microbes. This work proposes a Multi-View Feature Aggregation (MVFA) scheme that integrates the linear and nonlinear features to identify disease-related microbes. We introduce a non-negative matrix tri-factorization (NMTF) model to extract linear features for diseases and microbes. Then we learn another type of linear feature by utilizing a bi-random walk model. The nonlinear feature is obtained by inputting the two kinds of linear features into a capsule neural network. These three types of features describe the associations between diseases and microbes from different views. Finally, considering the complementary of these features, we leverage a logistic regression model to combine the NMTF model predictions, bi-random walk model predictions, and the capsule neural network predictions to obtain the final microbe-disease pair scores. We apply our method to predict human microbe-disease associations on two datasets. Experimental results show that our multi-view model outperforms the state-of-the-art models. The ablation study shows that aggregating multi-view linear and nonlinear features can improve the prediction performance.

Cancer is thought to be caused by the accumulation of driver genetic mutations. Therefore, identifying cancer driver genes plays a crucial role in understanding the molecular mechanism of cancer and developing precision therapies and biomarkers. In this work, we propose a Multi-Task learning method, called MTGCN, based on the Graph Convolutional Network to identify cancer driver genes. First, we augment gene features by introducing their features on the protein-protein interaction (PPI) network. After that, the multi-task learning framework propagates and aggregates nodes and graph features from input to next layer to learn node embedding features, simultaneously optimizing the node prediction task and the link prediction task. Finally, we use a Bayesian task weight learner to balance the two tasks automatically. The outputs of MTGCN assign each gene a probability of being a cancer driver gene. Our method and the other four existing methods are applied to predict cancer drivers for pan-cancer and some single cancer types. The experimental results show that our model shows outstanding performance compared with the state-of-the-art methods in terms of the area under the Receiver Operating Characteristic (ROC) curves and the area under the precision-recall curves. The MTGCN is freely available via https://github.com/weiba/MTGCN.

The rainfall infiltration model plays a key role in the fields of seepage theory and geological hazard evaluation. To reflect the change in the moisture content in soil during rainfall infiltration, the infiltration process was segmented into stages, and an improved unsaturated wetting front extension model was proposed by introducing unsaturated soil parameters on the basis of the traditional infiltration model. The variation rules of surface moisture content and wetting front depth were revealed under the condition of uniform or non-uniform moisture content distribution in soil. The results indicate that the surface moisture content and wetting front depth increase nonlinearly with time during the infiltration process, and the proposed model is in good agreement with the numerical simulation results, the maximum error is less than 5%, while the growth rate under two hypotheses shows obvious differences for different rainfall intensities. Moreover, due to the variation in the moisture content with time, the proposed model calculates a lower moisture content than that of the traditional model under the same conditions, but the expansion depth of the wetting front is higher and the range of influence on soil is greater.

This paper presents a case of Gaojiayuan subway station of Beijing Subway Line 14 constructed using combined shield and shallow tunnelling method. The layout, geological and hydrogeological conditions, construction process and related measures to accelerate construction speed and safeguard ground stability of the station are illustrated. The ground surface settlements of the subway station due to construction were systematically monitored. The monitoring results showed that the surface settlements were mainly caused by shield tunnelling, side drifts excavation and double arch excavation. The surface settlement above the station crown of a cross section induced by the above-mentioned three construction stages accounted for about 3.45–7.28%, 35.65–45.54%, 51.01–57.40% of the total settlement value. Limit surface settlement was produced due to the installation of jet grouting columns and cast-in-place piles, and the settlement could be effectively controlled after the completion of pile-beam-arch-wall system. It is noted that grouting can effectively compensate the ground loss and heave the ground accordingly. Moreover, due to the inherent complexity of the subway station construction, the surface settlement curve in a section fluctuated and no longer followed the Gaussian distribution.

The slurry type shield method is an important tunnelling method, especially for underwater tunnels in soft soil. If the slurry pressure is too high, it may lead to slurry fracturing of the stratum in front of the excavation face and cause water inrush accidents. Controlling the face stability of shallow shield tunnels is difficult owing to the inadequate understanding of the slurry induced fracturing mechanism. Most importantly, understanding the details of the slurry fracturing propagation process is not enough, as the process is especially complicated. However, the propagation process cannot be directly observed in the field or in small-scale laboratory tests because it occurs in bodies of soil. Thus far, an effective approach to investigate the slurry fracturing mechanism in the surrounding stratum of a slurry shield tunnel has not been reported. In this paper, a numerical simulation method for evaluating tunnelling-induced slurry fracturing is presented. The developed numerical model considered the couplings of stress distribution, fluid flows, and fracturing. The fracture initiation, branching, and propagation in the stratum could be reproduced numerically. A series of simulations for different ratios of cover depth to tunnel diameter were carried out to investigate the propagation process of slurry fracturing. The effects of slurry pressure at the tunnelling face and the cover depth above the tunnel were investigated. The results of the fracturing process induced by slurry, such as the fracture propagation velocity, slurry pressure distribution along the fracture, fracture initiation pressure, fracture extending pressure, and stratum deformations, were analyzed.

Understanding the breakage feature of granules has been an important study focus throughout the world for many years. The breakage mode depends on the extent of plastic flow, which cannot be explained by elastic solutions. In the paper, a numerical approach to particle breakage considering elastic-plastic behaviour is achieved using Finite Element Method (FEM). The numerical approach is validated by simulating the Brazilian test with a three-dimensional disk specimen. Then the breakage processes of spherical particle under compression are numerically modeled. The influence of different material mechanical properties is investigated and the consequences with respect to breakage processes are discussed. The predicted trends are in good agreement with experimental observations. The approach offers an effective way to investigate the breakage behaviour of granule, which would be helpful to make clear the whole process of the breakage mechanism.

A numerical approach for simulation of magma intrusion process, considering the couplings of the stress distribution, the viscous fluid flow of magma, and the fracturing of host rock, has been developed to investigate the mechanisms of fracture initiation and propagation in host rock during magma intrusion without pre-placing a set of fractures. The study focused on the dike intrusions filled with injected viscous magma in shallow sediments. A series of numerical modellings were carried out to simulate the process of magma intrusion in host rocks, with particular attention on the magma propagation processes and the formation of intrusion shapes. The model materials were Mohr-Coulomb materials with tension failure and shear failure. The scenarios of both stochastically heterogeneous host rocks and layered host rocks were analyzed. The injected magma formed intrusions shapes of (a) dyke, (b) sill, (c) cup-shaped intrusion, (d) saucer-shaped intrusion. The numerical results were in agreement with the experimental and field observed results, which confirmed the adequacy and the power of the numerical approach.

To investigate the fatigue behaviours of tunnel secondary lining under the aerodynamic effects produced by the running high-speed railway (HSR) trains, we proposed a dual fatigue damage accumulation model (DFDAM). In our model, a nonlinear variable load model was nested inside an equal-damage nonlinear model. The nonlinear variable load model was used to calculate the fatigue damage of a tunnel secondary lining after a single HSR train travelled through the tunnel, and the equal-damage nonlinear model was adopted to calculate the fatigue damage after multiple HSR trains travelled through the tunnel. Our proposed model was verified by comparison with laboratory fatigue testing results obtained by other researchers. The proposed model was also used to study the aerodynamic fatigue behaviours of a practical HSR tunnel project. The results show that the damage accumulation produced during the train running inside the tunnel is approximately the same as that of after an HSR train tail leaves the tunnel exit. Thus, after an HSR train leaves the tunnel exit, the influences of the aerodynamic pressure on the tunnel secondary lining cannot be ignored. The damage accumulation of a tunnel secondary lining associated with multiple HSR trains passing increases monotonically with the increase of the consumed life fraction. In contrast, the residual life of the fatigue damage decreases monotonically. This study can serve as a reference for studying the operational safety of HSR tunnels.

This paper investigates the influence of non-uniform corrosion of the mild steel reinforcement on the cracking propagation of the concrete cover. Partial surface of the reinforcement was coated by an epoxy resin in order to prevent the covered surface of the steel from corrosion. As a result, the reinforcement was corroded partially along the surface by an impressed current in this way. The corrosion propagation of the steel reinforcement and the corrosion-induced cracking process was investigated during different corrosion periods. The width and the cracking paths were observed carefully. The results showed that two cracking paths would happen to the concrete cover due to the non-uniform corrosion of the steel reinforcement, including the corrosion-induced crack along the radius direction of the concrete cover and two branches in the secant direction of the corrosion zone. The aggregate of the concrete could also influence the propagation of the cracking path significantly.

Conventional two-field mortar methods have master/slave bias and need special treatments for the cross corner problem. In this work, we present a three-field dual mortar method, which employs an intermediate interface to connect individual subdomains with nonconforming meshes. Using this intermediate interface as the master face, a dual mortar method can be formulated by discretizing Lagrange multipliers on the subdomain interfaces using dual basis functions. Furthermore, the computational cost is minimized by static condensation of Lagrange multipliers and elimination of displacement unknowns on subdomain interfaces. Owing to the three-field formulation, the presented method is free of master/slave bias and can handle the cross corner problem naturally. The stability condition for the intermediate interface mesh is investigated by theoretical analysing and numerical modelling. Numerical tests show that the presented method has optimal convergence rate and allows great flexibility in mesh preparation.

Numerical simulations with finite element method were carried out and five types of patterns of shear bands and their process of self-organization were obtained. The elasto-plastic theory of constitutive relationship with the non-associated flow rule, vertex-like yielding surfaces and strain softening of strength were adopted to describe the mechanical behavior of geomaterials of rock or soil. The non-symmetrical matrix due to the adoption of the non-associated flow rule was solved with the algorithm of dynamical relaxation of finite element method. The discrete or banded patterns of shear strain in the form of superlattice, parallel strips, super lattice turned parallel strips, rhomboid net and concentric rhomboid loops, were gradually formed as the loading increased. The mechanism of the structural pattern generation and the process of pattern self-organization in geomaterials of rock and soil were a process of mechanical equilibrium of stresses and the allocation of material deformation between the elastic sites and plastic sites. The approach provided a way for researching mechanical origin of shear band pattern.

Embryonic Six2-positive nephron progenitor cells adjacent to ureteric bud tips ultimately give rise to nephron structures, including proximal and distal tubules, podocytes, Bowman's capsules, and the glomeruli. This process requires an internal balance between self-renew and differentiation of the nephron progenitor cells, which is mediated by numerous molecules. Recent studies have shown that the neurofibromin (Nf1) null mutant mouse embryos have an 18- to 24-h developmental delay in metanephros manifesting retardation in its cephalad repositioning and reduction number of glomeruli. However, the underlying inter-/intracellular signaling mechanisms responsible for reducing number of glomeruli during nephrogenesis remain to be fully elucidated. Here, we originally detected the Nf1 expression in developing kidney and metanephric mesenchyme cells. Surprisingly, Nf1 knockdown by small interfering RNAs in the metanephric mesenchyme cells (mK3) resulted in a decreased expression of Six2, the key marker of renal progenitor cells, while the ratio of apoptotic cells was significantly increased. Furthermore, overexpression of Six2 in mk3 cells partially rescued apoptosis phenotype. Collectively, these results implied that knockdown of Nf1 resulted in apoptosis of mK3 cells in vitro probably through down-regulation of Six2 expression. Collectively, we demonstrated that down-regulated Six2 by knockdown of Nf1 resulted in apoptosis of mK3 cells in vitro. These results implied that inhibition of Nf1 may delay metanephros development via down-regulation of Six2.

Background.Ex vivoculture of intact embryonic kidney has become a powerful system for studying renal development. However, few methods have been available for gene manipulation and have impeded the identification and investigation of genes in this developmental process.Results. Here we systemically compared eight different serotypes of pseudotyped self-complementary adenoassociated viruses (scAAVs) transduction in cultured embryonic kidney with a modified culture procedure. We demonstrated that scAAV was highly effective in delivering genes into and expressing in compacted tissues. scAAV serotypes 2 and 8 exhibited higher efficiency of transduction compared to others. Expression kinetics assay revealed that scAAV can be used for gene manipulation at the study of UB branching and nephrogenesis. Repressing WT1 in cultured kidney using shRNA impairs tubule formation. We for the first time employed and validated scAAV as a gene delivery tool in cultured kidney.Conclusions. These findings are expected to expedite the use of theex vivoembryonic kidney cultures for kidney development research. For otherex vivocultured organ models, scAAV could also be a promising tool for organogenesis study.

Purpose Apolipoprotein E knockout (apoE−/−) mouse is one of the most popular models for cardiovascular research, especially in the study of atherosclerosis. Naturally, large amount of studies try to uncover the role of apoE in atherosclerosis, and indeed apoE plays an important role in this pathogenesis. Kidney is an organ that contains lots of capillaries and also largely expresses apoE. Moreover, a protective role of apoE in kidney as an autocrine regulator has been demonstrated previously, however, the underlying mechanism is largely unknown. Experimental design In this study, comparative proteomics is for the first time used to identify the differential proteins in kidneys of apoE−/− and wild type mice, respectively, and we try to reveal the signaling network of apoE in mice kidney using bioinformatics analysis. Results Our findings show that approximately 80 proteins are significantly differentially expressed in kidneys of apoE−/− and wild type mice, and the signaling network correlated to apoE is successfully established by employing bioinformatics assay. Conclusions and clinical relevance Taken together, we originally identify the proteins with differential expression and propose an apoE correlated molecular network in mice kidney. These findings further provide evidence of the role of apoE in mice kidney and a brand new perspective in the protection and treatment of kidney disease.

Autosomal recessive polycystic kidney disease (ARPKD), characterized by ectatic collecting duct, is an infantile form of PKD occurring in 1 in 20 000 births. Despite having been studied for many years, little is known about the underlying mechanisms. In the current study, we employed, for the first time, a MS-based comparative proteomics approach to investigate the differently expressed proteins between kidney tissue samples of four ARPKD and five control individuals. Thirty two differently expressed proteins were identified and six of the identified protein encoding genes performed on an independent group (three ARPKD subjects, four control subjects) were verified by semi-quantitative RT-PCR, and part of them were further validated by Western blot and immunohistochemistry. Moreover, similar alteration tendency was detected after downregulation of PKHD1 by small interfering RNA in HEK293T cell. Interestingly, most of the identified proteins are associated with mitochondria. This implies that mitochondria may be implicated in ARPKD. Furthermore, the String software was utilized to investigate the biological association network, which is based on known and predicted protein interactions. In conclusion, our findings depicted a global understanding of ARPKD progression and provided a promising resource of targeting protein, and shed some light further investigation of ARPKD.

High mobility group (HMG)-box proteins, a large and functionally diverse superfamily of architectural protein, are involved in the regulation of DNA-dependent processes such as transcription, replication and DNA repair via the HMG-box domain. Bobby sox homolog (BBX), a newly identified HMG-Box protein, may function as a sequence-specific transcription factor. However, its expression pattern and biological functions are largely unknown. In this work, phylogenetic analysis showed that BBX is highly conserved and belongs to a novel subfamily of HMG-Box superfamily together with CIC (capicua homolog). Real time RT-PCR and whole-mount in situ hybridization in zebrafish embryo revealed that bbx, cica, and cicb were maternally highly expressed from 4 cell to 1K cell stage, and the zygote expression was primarily distributed in the central nervous system (CNS) from 24 to 60 h post-fertilization (hpf). Immunohistochemistry analysis in mouse brain revealed that BBX was weakly expressed in the cerebellum and highly expressed in the cortex and hippocampus. These findings indicate that as a novel HMG-box protein, BBX maybe associated with CNS development and provides useful clues to further study of its biological functions.

Fibroblast growth factor 21 (FGF21) is a novel metabolic regulator. The present study aimed to investigate the effect of FGF21 on cholesterol efflux and the expression of ATP binding cassette (ABC) A1 and G1 in human THP-1 macrophage-derived foam cells. Furthermore, the present study aimed to investigate the role of the liver X receptor (LXR) α in this process. A model of oxidized low-density lipoprotein-induced foam cells from human THP-1 cells was established. The effect of FGF21 on cholesterol efflux was analyzed using a liquid scintillation counter. The expression of ABCA1 and ABCG1 was determined using quantitative polymerase chain reaction and western blot analyses. FGF21 was found to enhance apolipoprotein A1- and high-density lipoprotein-mediated cholesterol efflux. FGF21 was also observed to increase the mRNA and protein expression of ABCA1 and ABCG1. Furthermore, LXRα-short interfering RNA attenuated the stimulatory effects induced by FGF21. These findings suggest that FGF21 may have a protective effect against atherosclerosis by enhancing cholesterol efflux through the induction of LXRα-dependent ABCA1 and ABCG1 expression.

MicroRNAs (miRNAs) are small non-coding RNAs that down-regulate gene expression by binding to target mRNA for cleavage or translational repression, and play important regulatory roles in renal development. Despite increasing genes have been predicted to be miRNA targets by bioinformatic analysis during kidney development, few of them have been verified by experiment. The objective of our study is to identify the miRNAs targeting Six2, a critical transcription factor that maintains the mesenchymal progenitor pool via self-renewal (proliferation) during renal development. We initially analyzed the 3′UTR of Six2 and found 37 binding sites targeted by 50 putative miRNAs in the 3′UTR of Six2. Among the 50 miRNAs, miR-181b is the miRNAs predicted by the three used websites. In our study, the results of luciferase reporter assay, realtime-PCR and Western blot demonstrated that miR-181b directly targeted on the 3′UTR of Six2 and down-regulate the expression of Six2 at mRNA and protein levels. Furthermore, EdU proliferation assay along with the Six2 rescue strategy showed that miR-181b suppresses the proliferation of metanephric mesenchymal by targeting Six2 in part. In our research, we concluded that by targeting the transcription factor gene Six2, miR-181b inhibits the proliferation of metanephric mesenchymal cells in vitro and might play an important role in the formation of nephrons.

Hepatocellular carcinoma (HCC) is one of the most deadly diseases; metastasis and recurrence are the most important factors that affect the therapy of HCC chronically. Until now, the prognosis for the metastasis of HCC had not improved. Recently, several proteins that are related to metastasis and invasion of HCC were identified, but the effective markers still remain to be elucidated.In this study, comparative proteomics was used to study the differentially expressed proteins in two HCC cell lines MHCC97L and HCCLM9, which have low and high metastatic potentials, respectively.Our findings indicated that filamin A (FLNA) and phosphoglycerate kinase 1 (PGK1) were two significantly differentially expressed proteins, with high expression in HCCLM9 cells, and may influence the metastasis of HCC cells.Taken together with the confirmation of expression on the mRNA level, we propose the use of FLNA and PGK1 as potential markers for the progression of HCC.

Multiple lines of evidence have shown that the functional defect of pancreatic beta cells is the root cause of type 2 diabetes. FoxO1, a key transcription factor of fundamental cellular physiology and functions, has been implicated in this process. However, the underlying molecular mechanism is still largely unknown. Here, we show that the overexpression of FoxO1 promotes the proliferation of cultured pancreatic beta cells exposed to low nutrition, while no change in apoptosis was observed compared with the control group. Moreover, by using two specific inhibitors for PI3K and MAPK signaling, we found that FoxO1 might be the downstream transcription factor of these two pathways. Furthermore, a luciferase assay demonstrated that FoxO1 could regulate the expression of Ccnd1 at the transcription level. Collectively, our findings indicated that FoxO1 modulated by both MAPK and PI3K signaling pathways was prone to cause the proliferation, but not the apoptosis, of pancreatic beta cells exposed to low nutrition, at least partially, by regulating the expression of Ccnd1 at the transcription level.

Trpp5 is one member of the polycystic kidney disease (PKD) family, which belongs to transient receptor potential (TRP) superfamily. Our previous study has shown that Trpp5 is developmentally expressed in mouse testis and overexpression of Trpp5 increases intracellular free calcium concentration in MDCK cells. However, the roles of this protein in cellular processes are largely unknown. Here, we demonstrated that Trpp5 resided in both cytoplasm and cell membrane of HEK293 cells. We found that overexpression of Trpp5 slightly increased the calcium current amplitude of HEK293 cells and shifted the reversal potential to a more negative value. Meanwhile, overexpression of Trpp5 suppressed proliferation of Hela cells via inhibiting DNA replication and induced apoptosis of Hela cells with morphological changes and accumulation of fragmented DNA. Collectively, these findings suggest that Trpp5 might involve calcium homeostasis contributing to cell proliferation and apoptosis.

Data mining has been applied to CRM (Customer Relationship Management) in many industries with a limited success. Most data mining tools can only discover customer models or profiles (such as customers who are likely attritors and customers who are loyal), but not actions that would improve customer relationship (such as changing attritors to loyal customers). We describe a novel algorithm that suggests actions to change customers from an undesired status (such as attritors) to a desired one (such as loyal). Our algorithm takes into account the cost of actions, and further it attempts to maximize the expected net profit. To our best knowledge, no data mining algorithms or tools today can accomplish this important task in CRM. The algorithm is implemented, with many advanced features, in a specialized and highly effective data mining software called Proactive Solution.