Integrative bioinformatics approaches to establish potential prognostic immune-related genes signature and drugs in the non-small cell lung cancer microenvironment

Introduction: Research has revealed that the tumor microenvironment (TME) is associated with the progression of malignancy. The combination of meaningful prognostic biomarkers related to the TME is expected to be a reliable direction for improving the diagnosis and treatment of non-small cell lung cancer (NSCLC).Method and Result: Therefore, to better understand the connection between the TME and survival outcomes of NSCLC, we used the “DESeq2” R package to mine the differentially expressed genes (DEGs) of two groups of NSCLC samples according to the optimal cutoff value of the immune score through the ESTIMATE algorithm. A total of 978 up-DEGs and 828 down-DEGs were eventually identified. A fifteen-gene prognostic signature was established via LASSO and Cox regression analysis and further divided the patients into two risk sets. The survival outcome of high-risk patients was significantly worse than that of low-risk patients in both the TCGA and two external validation sets (p-value < 0.05). The gene signature showed high predictive accuracy in TCGA (1-year area under the time-dependent ROC curve (AUC) = 0.722, 2-year AUC = 0.708, 3-year AUC = 0.686). The nomogram comprised of the risk score and related clinicopathological information was constructed, and calibration plots and ROC curves were applied, KEGG and GSEA analyses showed that the epithelial-mesenchymal transition (EMT) pathway, E2F target pathway and immune-associated pathway were mainly involved in the high-risk group. Further somatic mutation and immune analyses were conducted to compare the differences between the two groups. Drug sensitivity provides a potential treatment basis for clinical treatment. Finally, EREG and ADH1C were selected as the key prognostic genes of the two overlapping results from PPI and multiple Cox analyses. They were verified by comparing the mRNA expression in cell lines and protein expression in the HPA database, and clinical validation further confirmed the effectiveness of key genes.Conclusion: In conclusion, we obtained an immune-related fifteen-gene prognostic signature and potential mechanism and sensitive drugs underling the prognosis model, which may provide accurate prognosis prediction and available strategies for NSCLC

High-speed Packet Capture Mechanism Based on Zero-copy in Linux

The development of gigabit-network demand higher standard of the packet capture's efficiency. Traditional network packet capture mechanisms get poor performance when used in gigabit-network. So we proposed a new network packet capture mechanism using zero-copy and POLLING. Through the modification to the bottom-layer, we achieve the packet capture in user space, and bypass the intervention of operating system's kernel. The efficiency of data processing is improved We achieve wire-speed capture rate, and the CPU usage rate is below 10%

Transformational dynamics of BZO and BHO nanorods imposed by Y2O3 nanoparticles for improved isotropic pinning in YBa2Cu3O7−δ thin films

An elastic strain model was applied to evaluate the rigidity of the c-axis aligned one-dimensional artificial pinning centers (1D-APCs) in YBa2Cu3O7-δ matrix films. Higher rigidity was predicted for BaZrO3 1D-APCs than that of the BaHfO3 1D-APCs. This suggests a secondary APC doping of Y2O3 in the 1D-APC/YBa2Cu3O7-δ nanocomposite films would generate a stronger perturbation to the c-axis alignment of the BaHfO3 1D-APCs and therefore a more isotropic magnetic vortex pinning landscape. In order to experimentally confirm this, we have made a comparative study of the critical current density Jc (H, θ, T) of 2 vol.% BaZrO3 + 3 vol.%Y2O3 and 2 vol.%BaHfO3 + 3 vol.%Y2O3 double-doped (DD) YBa2Cu3O7-δ films deposited at their optimal growth conditions. A much enhanced isotropic pinning was observed in the BaHfO3 DD samples. For example, at 65 K and 9.0 T, the variation of the Jc across the entire θ range from θ=0 (H//c) to θ=90 degree (H//ab) is less than 18% for BaHfO3 DD films, in contrast to about 100% for the BaZrO3 DD counterpart. In addition, lower α values from the Jc(H) ∼ H-α fitting were observed in the BaHfO3 DD films in a large θ range away from the H//c-axis. Since the two samples have comparable Jc values at H//c-axis, the improved isotropic pinning in BaHfO3 DD films confirms the theoretically predicted higher tunability of the BaHfO3 1D-APCs in APC/YBa2Cu3O7-δ nanocomposite films

Nomograms predict prognosis and hospitalization time using non-contrast CT and CT perfusion in patients with ischemic stroke

BackgroundStroke is a major disease with high morbidity and mortality worldwide. Currently, there is no quantitative method to evaluate the short-term prognosis and length of hospitalization of patients.PurposeWe aimed to develop nomograms as prognosis predictors based on imaging characteristics from non-contrast computed tomography (NCCT) and CT perfusion (CTP) and clinical characteristics for predicting activity of daily living (ADL) and hospitalization time of patients with ischemic stroke.Materials and methodsA total of 476 patients were enrolled in the study and divided into the training set (n = 381) and testing set (n = 95). Each of them owned NCCT and CTP images. We propose to extract imaging features representing as the Alberta stroke program early CT score (ASPECTS) values from NCCT, ischemic lesion volumes from CBF, and TMAX maps from CTP. Based on imaging features and clinical characteristics, we addressed two main issues: (1) predicting prognosis according to the Barthel index (BI)–binary logistic regression analysis was employed for feature selection, and the resulting nomogram was assessed in terms of discrimination capability, calibration, and clinical utility and (2) predicting the hospitalization time of patients–the Cox proportional hazard model was used for this purpose. After feature selection, another specific nomogram was established with calibration curves and time-dependent ROC curves for evaluation.ResultsIn the task of predicting binary prognosis outcome, a nomogram was constructed with the area under the curve (AUC) value of 0.883 (95% CI: 0.781–0.985), the accuracy of 0.853, and F1-scores of 0.909 in the testing set. We further tried to predict discharge BI into four classes. Similar performance was achieved as an AUC of 0.890 in the testing set. In the task of predicting hospitalization time, the Cox proportional hazard model was used. The concordance index of the model was 0.700 (SE = 0.019), and AUCs for predicting discharge at a specific week were higher than 0.80, which demonstrated the superior performance of the model.ConclusionThe novel non-invasive NCCT- and CTP-based nomograms could predict short-term ADL and hospitalization time of patients with ischemic stroke, thus allowing a personalized clinical outcome prediction and showing great potential in improving clinical efficiency.SummaryCombining NCCT- and CTP-based nomograms could accurately predict short-term outcomes of patients with ischemic stroke, including whose discharge BI and the length of hospital stay.Key ResultsUsing a large dataset of 1,310 patients, we show a novel nomogram with a good performance in predicting discharge BI class of patients (AUCs > 0.850). The second nomogram owns an excellent ability to predict the length of hospital stay (AUCs > 0.800)

China's Culture

170 hal.;22 c

A Content Authentication Scheme in Hybrid P2P Network

In P2P file sharing network, the replicas of the same content are stored at various locations. This allows content to be accessed even when some nodes are disconnected. However, this high degree of redundancy implies that it is necessary to find some security mechanisms in order to avoid attacks based on content pollution. In this paper, we propose a content authentication method for hybrid P2P network. For it is unrealistic to apply a trusted third party in P2P network, our scheme relies on a set of up-layer nodes playing the role of a certificate authority in hybrid P2P network. In our scheme, we use Merkle Hash Tree and Certificateless Threshold Ring Signature to authenticate the integrality of content. Foremost, the threshold ring signature based on certificateless public key cryptology scheme is firstly mentioned in this paper. Finally, we solve the problems about fault tolerant storage the authentication information and the digital signature resists replay attack.

A Novel Seepage Safety Monitoring Model of CFRD with Slab Cracks Using Monitoring Data

The traditional regression model usually simulates the influence of water pressure and rainfall in the early stage based on experience, but it is not suitable. To solve this problem, the normal distribution curve is used to simulate the lagging effect of water pressure and rainfall on dam seepage. In view of problem of slab cracks, the influence of cracks on seepage is analyzed. In this paper, a safety monitoring model for concrete face rockfill dam (CFRD) seepage with cracks considering the lagging effect is proposed, in which slab cracks are considered as an influencing factor. The radial basis function neural network (RBFNN) optimized by genetic algorithm (GA) is used to establish a safety monitoring model for a CFRD seepage. Seepage of the dam is predicted by this model, whose results are similar to the monitoring data, which indicates that the method has certain applicability. Through the analysis of the proportion of factors affecting CFRD seepage, it is found that the rainfall component has the greatest impact on the total seepage, accounting for more than 50%, and the crack component accounts for about 10%. Finally, through the cloud model, the monitoring index of CFRD seepage is worked out, which has certain guiding significance for the treatment of abnormal seepage monitoring data

Application of Spatiotemporal Hybrid Model of Deformation in Safety Monitoring of High Arch Dams: A Case Study

As an important feature, deformation analysis is of great significance to ensure the safety and stability of arch dam operation. In this paper, Jinping-I arch dam with a height of 305 m, which is the highest dam in the world, is taken as the research object. The deformation data representation method is analyzed, and the processing method of deformation spatiotemporal data is discussed. A deformation hybrid model is established, in which the hydraulic component is calculated by the finite element method, and other components are still calculated by the statistical model method. Since the relationship among the measuring points is not taken into account and the overall situation cannot be fully reflected in the hybrid model, a spatiotemporal hybrid model is proposed. The measured values and coordinates of all the typical points with pendulums of the arch dam are included in one spatiotemporal hybrid model, which is feasible, convenient, and accurate. The model can predict the deformation of any position on the arch dam. This is of great significance for real-time monitoring of deformation and stability of Jinping-I arch dam and ensuring its operation safety