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As an important element in regulating the tumor microenvironment (TME), integrin plays a key role in tumor progression. This study aimed to establish prognostic signatures to predict the overall survival and identify the immune landscape of patients with lung adenocarcinoma based on integrins. The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus datasets were used to obtain information on mRNA levels and clinical factors (GSE72094). The least absolute shrinkage and selection operator (LASSO) model was used to create a prediction model that included six integrin genes. The nomogram, risk score, and time-dependent receiver operating characteristic analysis all revealed that the signatures had a good prognostic value. The gene signatures may be linked to carcinogenesis and TME, according to a gene set enrichment analysis. The immunological and stromal scores were computed using the ESTIMATE algorithm, and the data revealed, the low-risk group had a higher score. We discovered that the B lymphocytes, plasma, CD4+ T, dendritic, and mast cells were much higher in the group with low-risk using the CiberSort. Inflammatory processes and several HLA family genes were upregulated in the low-risk group. The low-risk group with a better prognosis is more sensitive to immune checkpoint inhibitor medication, according to immunophenoscore (IPS) research. We found that the patients in the high-risk group were more susceptible to chemotherapy than other group patients, according to the prophetic algorithm. The gene signatures could accurately predict the prognosis, identify the immune status of patients with lung adenocarcinoma, and provide guidance for therapy.

Implant-supported cement–screw-retained crowns combine the advantages of screw-retained and cement-retained crowns. However, the occlusal screw access hole interrupts porcelain integrity, which may...

Reasonable zirconia surface pretreatment results in excellent bond strength. This study compared the effects of different surface treatments on the shear bond strength of zirconia. A total of 48 zi...

In the research of social networks, their structural characteristics, user social behaviors, and user relationships are elements that are important to understand social networks, to predict user behaviors, and to manage social networks. In this article, we took as the research object of social networks the mobile communication network, which is closely connected with people’s real lives. We studied the structural characteristics using the complex network analysis methods and derived the laws that exist in the structure of communication social networks. We analyzed users’ social behaviors or social patterns from the perspective of age, gender, social scope, age differences, and time. In addition, we extracted various salient features of user’s calling behavior, and used the XGBoost and logistic regression (LR) fusion method to establish the Kinship-XL model, which is able to improve the performance and speed. Through the experimental verification, the Kinship-XL model can determine whether there is a kinship between users or not.

Unsupervised multi-modal hashing has recently attracted broad attention in research area of large-scale multimedia retrieval for its low storage cost, high retrieval speed, and independence on semantic labels. However, the model learning process of existing methods still suffer from the problem of low efficiency: 1) Many existing methods measure the contributions of different modalities using fixed modality weights. In order to avoid over-fitting, they need an inefficient hyper-parameter adjustment process. 2) Most existing methods adopt inefficient optimization strategies to learn hash codes. In this letter, we propose an unsupervised Efficient Parameter-free Adaptive Multi-modal Hashing (EPAMH) model to adaptively capture the modality variations and preserve the discriminative semantics of multi-modal features into the binary hash codes. Moreover, we directly learn the binary codes with simple and efficient operations, which prevents the relaxing quantization errors and improves the model learning efficiency. Experiments prove the superior performance of EPAMH on three public multimedia retrieval datasets. Our source codes and testing datasets can be obtained at https://github.com/ChaoqunZheng/EPAMH .

Carbon fiber reinforced plastics (CFRP) plates are gradually replacing steel in the aerospace and automotive sectors due to their high specific gravity and strength. In service, the material is assembled in the form of a shell riveted or bolted to the selected substrate to ensure that the material is firmly connected to the surface. In this paper, we present detection of hole-cracks phenomenon by using low-frequency ultrasonic guided wave to monitor the health state of CFRP plate structure. The excellent magneto-strictive (transducer) coupling characteristics of Galfenol material and the dispersion equations for Lamb and SH0 wave were solved by using COMSOL software. The ultrasonic transducer was designed for excitation of low-frequency guided wave. Thus, convected wave equation simulation and experiment verified that super transducer and stimulate the Lamb wave (S0), mode wave (A0), feasibility wave (SH0). Then, based on the magnetic circuit Ohm's law and the driving magnetic field required by Galfenol, the sizes of each component and the relevant parameters have been designed. In order to improve the propagation energy of Lamb wave in the crack damage detection, an optimization convected wave method is used for defect determination. Simulation results show that the particle displacement in CFRP plate is increased by 65.3% after optimization, which proves the effectiveness of the proposed convected wave method. Using ultrasonic guided wave and mechanical magneto-strictive technology to monitor the structure strength of the hole, the position and degree of damage can be obtained effectively. Lastly, the experiments werecompleted which determined that the defect position was critical and improved. The coordinate error is controlled fewer than 11.09%.

Background. Lung adenocarcinoma (LUAD), as the main subtype of lung cancer, is one of the common causes of cancer-related deaths worldwide. The AHNAK family is correlated with cell structure and migration, cardiac calcium channel signaling, and tumor metastasis. Previous studies showed AHNAK2 could promote tumor progression and cell migration in melanoma and renal clear cell carcinoma. However, the role of AHNAK2 in LUAD remains unknown. Methods. We examined the levels of AHNAK2 in pathological specimens and the database of Clinical Proteomic Tumor Analysis Consortium-Lung adenocarcinoma (CPTAC-LUAD), The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD), Gene Expression Omnibus dataset (GSE72094, GSE26939), and The Genotype-Tissue Expression (GTEx) of lung tissue samples. Univariate Cox regression, multivariate Cox regression, and Kaplan–Meier survival analysis were performed to reveal the relationship between AHNAK2 and prognosis. A nomogram was constructed to predict 2- or 3-year overall survival and validated via calibration curves, receiver operating characteristic (ROC) analysis, and decision curve analysis (DCA). Furthermore, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to explore the functional role of AHNAK2 in lung adenocarcinoma. Finally, by transfecting siRNA, we examined the regulatory effect of AHNAK2 on cell migration. Results. The expression of AHNAK2 was upregulated in tumor samples and correlated with poor prognosis in LUAD patients. Nomogram with AHNAK2 and clinical parameters showed a good prediction in overall survival (OS), especially the 2-year OS. In addition, functional analyses and wound healing assay suggested that AHNAK2 might be involved in the regulation of migration in LUAD. Conclusion. In summary, our study showed that AHNAK2 might be a novel biomarker in LUAD and revealed the potential mechanism of AHNAK2 in LUAD progression which could provide new insights for target therapy.

Cucurbit[6]uril-based monomer (CB[6]MA), hydrazide-based monomer (MH), and acrylamide (AM) were used to prepare copolymers (PAM-CB[6]MA-MH) by radical copolymerization. PAM-CB[6]MA-MH was complexed with 1-aminopyrene through non-covalent interactions, which resulted in thePAM-CB[6]MA-MH•1-Aminopyrene macromolecular complex. As a result, novel copolymeric systems with novel properties were obtained. In the presence of a glacial acetic acid catalyst (pH = 5) or under neutral pH conditions, PAM-CB[6]MA-MH was mixed with glyoxal solution to obtain self-repairing hydrogels. The hydrogels thus obtained showed pH reversible responsiveness. In addition, the PAM-CB[6]MA-MH•1-Aminopyrene macromolecular complex could effectively detect Cu2+ ions in aqueous solution, which expands the application scope of 1-aminopyrene in aqueous solution. The PAM-CB[6]MA-MH•1-Aminopyrene macromolecular hydrogel's efficient detection of Cu2+ ions makes it an effective portable platform with potential for the visual detection of Cu2+ ions.

Limited knowledge on the social laws for cell phone users is known due to the lack of public call data. In this paper, we collected data regarding more than 20 million users of the China Telecom Corporation and analyzed the power-law distribution and their social behavior laws. Two power-law distributions that exist in the distribution of degree and user contacts are found in the study of the users’ behaviors, and we analyzed the conclusions drawn from the study. Also, we studied the users’ social patterns based on the users’ age difference, and analyzed user’s social behaviors from the user’s age, gender, social scope, time and other aspects.

Social network user identification is of great value and significance for predicting users’ behavior, analyzing and regulating social networks, and studying the interaction between users. This paper studies the identities of social network users, divides them into organizational and individual users in terms of their identities, and explicitly defines and identifies both types of users. This paper also distinguishes a user as an organization or an individual according to the contents of text, multimedia, and their time series published in a social network. During the identification, the content (topic) complexity and normalization of the user in text content are measured; the picture features and time-series content of the user are being analyzed, and the machine-operable method that identifies a user as an organization or an individual is proposed from different perspectives so as to perform this identification. Finally, in order to verify the feasibility and effectiveness of the identification method proposed in this paper, an experiment was made to the data collected from Sina Weibo and the probability model identification method was used to make a comparative analysis. Results indicate that the identification method used in this paper can effectively distinguish between a user as an organization or an individual.

The performance of traveling jet trenching in stiff clay was tested. All the key parameters varied in the experiment, including the jet velocity, the shear strength of clay, the diameter of the noz...

In judicial adjudications, the chain of custody (or chain of evidence) is the core element of conviction. A complete chain of custody can provide a solid basis for judicial trials and sentencing. However, the evidence correlation analysis in the litigation process mainly depends on the judge's manual judgment, which often has the problems of poor interpretability and strong subjectivity. At present, the use of data mining technology to analyze the judicial data is of great significance and practical value in the construction of smart courts. This paper focuses on the problem of multi-factor modeling and reasoning about the trusted relationship between elements, and proposes an association probability analysis model based on multi-element fusion. Also, the process of obtaining the chain of custody of the judicial field is used to further illustrate the specific construction process of the model. Firstly, the factual decision chain is defined based on the knowledge of the judicial domain, and a multi-evidence association network is constructed, in which each evidence entity acts as a node in the network, and calculates the correlation probability between nodes through the association relationship between the evidence elements. Then, according to the event decision chain, the association constraint relationship between the evidences is established through the Bayesian network. Therefore, a multi-evidence association model is established, and all possible chain of custody combinations are obtained through genetic algorithm, so as to optimize the multi-evidence correlation model. Finally, the optimal chain of custody is obtained through the model. The validity of the model is verified by experiments in three types of cases on real data sets.

Virtual simulation technology has a broad application prospect in the field of simulation training, which can offset the high risk and cost problems brought by training, and greatly improve the quality and efficiency of training. This paper discusses the development of virtual simulation technology and its application in the field of simulation training, and puts forward some suggestions for the construction of virtual training system.

The description of user behavior in social networks is an important issue for studying social networks. Given that Petri nets can describe the resource flow problem, this study utilizes the features of Petri nets to portray the user behavior states during the message propagation of a micro-blog network and presents an information propagation formalized representation method of a micro-blog network. On this basis, this study analyzed the proposed formalized representation method in detail. We provide examples of applying formalized representation (e.g., micro-blog network addiction of users, user behavior influence, and public opinion analysis). In addition, we introduce the algorithms of formalized representation. We conduct experiments using Sina micro-blog data. Results show that the information propagation formalized representation method of micro-blog network based on Petri nets can depict user behaviors of micro-blog network intuitively and accurately. This study reveals a new perspective for information transmission of a micro-blog network and provides some tools to support public opinion monitoring and micro-blog marketing applications.

Background Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) play an important role in the competitive endogenous RNA (ceRNA) networks in that they regulate protein-coding gene expression by sponging microRNAs (miRNAs). However, the understanding of the ceRNA network in tongue squamous cell carcinoma (TSCC) remains limited. Methods Expression profile data regarding mRNAs, miRNAs and lncRNAs as well as clinical information on 122 TSCC tissues and 15 normal controls from The Cancer Genome Atlas (TCGA) database were collected. We used the edgR package to identify differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) between TSCC samples and normal samples. In order to explore the functions of DEmRNAs, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Subsequently, a ceRNA network was established based on the identified DElncRNAs–DEmiRNAs and DEmiRNAs–DEmRNAs interactions. The RNAs within the ceRNA network were analyzed for their correlation with overall disease survival. Finally, lncRNAs were specifically analyzed for their correlation with clinical features in the included TSCC patient samples. Results A total of 1867 mRNAs, 828 lncRNAs and 81 miRNAs were identified as differentially expressed in TSCC tissues (—log 2fold change— ≥ 2; adjusted P value P P Conclusion Our study deepens the understanding of ceRNA network regulatory mechanisms in TSCC. Furthermore, we identified ten lncRNAs (PART1, LINC00261, AL163952.1, C2orf48, FAM87A, LINC00052, LINC00472, STEAP3-AS1, TSPEAR-AS1 and ERVH48-1) as novel, potential prognostic biomarkers and therapeutic targets for TSCC.

Background Hepatocellular carcinoma (HCC) accounts for 75–80 % of primary liver cancer, and usually arises after years of liver disease. Thus it is important to understand the molecular mechanisms which drive or mediate the development of HCC.

The capability for DNA double-strand breaks (DSBs) repair is crucial for chromatin dramatic changes and DNA damage in normal and tumor cells. We have investigated the clinicopathological significance of DNA repair gene Ku70 expression in hepatocellular carcinoma. We demonstrated that Ku70 expression was significantly increased in HCC, and the high expression levels were significantly correlated with gender, maximal tumor size, HBsAg status, tumor nodule number, distant metastasis and Ki-67 expression by clinicopathological analysis. The Kaplan-Meier survival curves revealed that increasing Ku70 expression was associated with poor prognosis in HCC patients. Ku70 expression was an independent prognostic marker of overall HCC patient survival in a multivariate analysis. In addition, through serum starvation and refeeding, we found that Ku70 was lowly expressed in serum-starved Huh7 and HepG2 HCC cells, and was progressively increased after serum-additioning. Furthermore, knockdown of Ku70 inhibited cell proliferation accompanying an increase in p27(kip1) levels through interacting with FOXO4. These findings provide a rational framework for the progression of HCC and could be a potential molecular therapy by targeting the Ku70-FOXO4 interaction.

Zhang, S.; Zhao, M.; Ge, T., and Wang, C., 2016. Experimental research on trenching in stiff clay by submerged vertical traveling jets. This study investigated trenching by submerged circular traveling jets in stiff clay using an experimental method. The testing clay was prepared as mixtures of natural clay and cement with shear strength ranging from 60 kPa to 90 kPa. The jet pressure, the nozzle translational velocity, and the diameter of the nozzle all varied in the test. A cohesive sediment scouring theory was employed to reveal the mechanism of the jet trenching. It showed that the boundary layer shear force on the jet-soil interface might be the predominant mobilizing force for jet trenching. The trench depth was found to increase with the jet pressure, erodibility coefficient, and the diameter of the nozzle and decrease with the translational velocity of the nozzle and the threshold stress of the clay. The essence of the traveling jet trenching could be considered as jet erosion. The effici...

Trenching depth calculation of traveling jet is a very important field in both pipeline burying and dredging engineering. The trenching ability of a noncontact control flow jet trencher was predicted by experimental method according to the geometry similarity. In the test, the jet pressure, the shear strength of clay, and the translational speed of nozzle were the same with the design parameters, while the nozzle was a reduced scale model. The trenching depth was found about seven to nine times of the nozzle’s diameter. The width of the trench was about four times of the nozzle’s diameter. Based on the test results the noncontact jet trencher was produced and succeeded in practical usage.

This paper expounds the root of complexity of system-of-systems combat, and summarizes the methodology and technical route of complex system-of- systems combat experiment. Then, this paper studies the framework of system countermeasure experiment, and points out the technical difficulties of system countermeasure experiment.

Based on the comprehensive analysis of the components of simulation training, the whole process and systematic evaluation and analysis of the effect of simulation training are carried out in three aspects: the group training ability of the group trainer, the expected degree that the simulation training system meets the simulation training and the training effect of the trainee, and the corresponding evaluation index system is established.

Paths and cycles are the two pivotal elements in a network. Here, we demonstrate that paths, particularly the shortest ones, are incomplete in information network. However, based on such paths, many network centrality measures are designed. While extensive explorations on paths have been made, modest studies focus on the cycles on measuring network centrality. We study the relationship between the shortest cycle and the shortest path from extensive real-world networks. The results illustrate the incompleteness of the shortest paths on measuring network centrality. Noticing that the shortest cycle is much more robust than the shortest path, we propose two novel cycle-based network centrality measures to address the incompleteness of paths: the shortest cycle closeness centrality (SCC) and the all cycle betweenness centrality (ACC). Notwithstanding we focus on the network centrality problem, our findings on cycles can be applied to explain the incompleteness of paths in applications and could improve the applicability into more scenarios where the paths are employed in network science.

Src associated in mitosis (Sam68; 68 kDa) is a KH domain RNA-binding protein that belongs to the signal transduction and activation of RNA family, and has been implicated in the oncogenesis and progression of several human cancers. Our study aimed to investigated the clinicopathologic significance of Sam68 expression and its role in cell proliferation and the underlying molecular mechanism in hepatocellular carcinoma (HCC). We demonstrated that Sam68 expression was significantly increased in HCC and high expression of Sam68 was significantly associated with Edmondson grade, tumor size, tumor nodule number, HBsAg status and Ki-67 expression. The Kaplan-Meier survival curves showed that increased expression of Sam68 was correlated with poor prognosis in HCC patients and served as an independent prognostic marker of overall survival in a multivariable analysis. In addition, through serum starvation and refeeding assay, we demonstrated that Sam68 was lowly expressed in serum-starved HCC cells, and was progressively increased after serum-additioning. Furthermore, siRNA knockdown of endogenous Sam68 inhibited cell proliferation and tumourigenicity of HCC cells in vitro, through blocking the G1 to S phase transition. Moreover, we reported that the anti-proliferative effect of silencing Sam68 was accompanied with up-regulated expression of cyclin-dependent kinase inhibitors, p21(Cip1) and p27(Kip1), enhanced transactivation of FOXO factors (FOXO4), and dysreuglation of Akt/GSK-3β signaling. Taken together, these findings provide a rational framework for the progression of HCC and thereby indicated that Sam68 might be a novel and useful prognostic marker and a potential target for human HCC treatment.

SYF2, also known as p29/NTC31/CBPIN, encodes a nuclear protein that interacts with Cyclin D-type binding-protein 1. SYF2 has been reported to be involved in pre-mRNA splicing and cell cycle regulation. In the present study, we observed that SYF2 was obviously upregulated in HCC tumor tissues and cell lines, and its level was positively correlated with the tumor grade and Ki-67 expression, as well as poor prognosis of HCC. In vitro, using serum starvation-refeeding experiment, our results suggested that SYF2 was upregulated in proliferating HCC cells, and was positive correlated with the expression of PCNA and Cyclin D1. In addition, depletion of SYF2 decreased PCNA and Cyclin D1 levels. Accordingly, interference of SYF2 resulted in cells cycle arrest at G1/S phase in Huh7 HCC cells. Furthermore, we found that SYF2 might interact with Cyclin D1 and could confer doxorubicin resistance in HCC cells. These findings revealed that SYF2 might play a regulatory role in the proliferation of HCC cells. In summary, SYF2 may be a novel prognostic marker and serve as a potential therapeutic target in HCC.

Hepatocellular carcinoma (HCC) is a major health concern with a high morbidity and mortality rate worldwide. However, the mechanism underlying hepatocarcinogenesis remains unclear. Forkhead box P2 (FOXP2) has been implicated in various human cancer types. However, the role of FOXP2 in HCC remains unknown. Western blot and immunohistochemistry were used to measure the expression of FOXP2 protein in HCC and adjacent normal tissues in 50 patients. Wound healing and transwell assays were used to determine the cell invasion ability. We showed that the level of FOXP2 was significantly reduced in HCC compared with the adjacent non-tumorous tissue. There was statistical significance between the expression of FOXP2 and vein invasion (P = 0.017), number of tumor nodes (P = 0.028), and AFP (P = 0.033). Low expression of FOXP2 correlated with poor survival. Moreover, wound healing and transwell assays showed that FOXP2 could decrease cell invasion and affect the expression of vimentin and E-cadherin. Our results suggested that FOXP2 expression was downregulated in HCC tumor tissues, and reduced FOXP2 expression was associated with poor overall survival. In addition, downregulation of FOXP2 significantly enhanced cell invasiveness. These findings uncover that FOXP2 might be a new prognostic factor and be closely correlated with HCC cell invasion.