The change of tribological behavior of zinc coatings with the reduction of grain size from micro to nano-scale is investigated.

A nanocrystalline zinc coating is produced by pulse reverse electrodeposition in a sulfate bath with polyacrylamide as the only additive and the mechanical, wear and corrosion resistance properties are evaluated.

No abstract

A hydrophobic protective corrosion product film (NC-1) with a nano-wire structure is formed on the surface of a nanocrystalline zinc coating.

The relationship between miR-21 and miR-182 gene expression in peripheral blood and gastric cancer tissue was investigated, exploring the relationship between the levels of miR-21 and miR-182 and prognosis of gastric cancer patients, and determining the effects of these two genes on the growth and migration of gastric cancer cells. Fifty gastric cancer patients who were treated in the 254th Hospital of PLA, from July 2012 to July 2014 were selected. Peripheral blood samples were drawn from patients, and 50 healthy subjects were studied as controls. The levels of the miR-21 and miR-182 genes were detected by semi-quantitative PCR, and the correlation between miR-21 and miR-182 expression and clinicopathological features was explored. Moreover, the effects of miR-21 and miR-182 expression on the survival time and prognosis of patients were investigated. siRNA was used to downregulate miR-21 and miR-182 gene expression in MGC-803 gastric cancer cells, and MTT and Transwell assays were conducted. As a result, the relative expression levels of miR-21 and miR-182 in peripheral blood of gastric cancer patients were significantly higher than in healthy subjects (p<0.01) and the relative expression of miR-182 was closely related to the clinicopathological features of gastric cancer patients (p<0.05); high expression of miR-21 and miR-182 was associated with reduced survival time of patients (p<0.05); MGC-803 cells with low expression of miR-21 and miR-182 were analyzed, showing that miR-182 promoted cell proliferation and migration (p<0.01). In conclusion, the relative levels of miR-21 and miR-182 in peripheral blood of patients with gastric cancer are significantly increased; low expression of miR-182 can significantly reduce the proliferation and migration of gastric cancer cells. Moreover, miR-182 expression, which is closely related to the clinicopathological features of gastric cancer, can serve as a target for the clinical treatment of gastric cancer.

Online novel recommendation recommends attractive novels according to the preferences and characteristics of users or novels and is increasingly touted as an indispensable service of many online stores and websites. The interests of the majority of users remain stable over a certain period. However, there are broad categories in the initial recommendation list achieved by collaborative filtering (CF). That is to say, it is very possible that there are many inappropriately recommended novels. Meanwhile, most algorithms assume that users can provide an explicit preference. However, this assumption does not always hold, especially in online novel reading. To solve these issues, a tag-driven algorithm with collaborative item modeling (TDCIM) is proposed for online novel recommendation. Online novel reading is different from traditional book marketing and lacks preference rating. In addition, collaborative filtering frequently suffers from the Matthew effect, leading to ignored personalized recommendations and serious long tail problems. Therefore, item-based CF is improved by latent preference rating with a punishment mechanism based on novel popularity. Consequently, a tag-driven algorithm is constructed by means of collaborative item modeling and tag extension. Experimental results show that online novel recommendation is improved greatly by a tag-driven algorithm with collaborative item modeling.

Background: Role of tumor-stroma ratio (TSR) as a predictor of survival in patients with non-small cell lung cancer (NSCLC) remains not clear. A systematic review and meta-analysis was conducted to summarize current evidence for the role of TSR in NSCLC.Methods: Relevant cohort studies were retrieved via search of Medline, Embase, and Web of Science databases. The data was combined with a random-effect model by incorporating the between-study heterogeneity. Specifically, subgroup and meta-regression analyses were performed to explore the association between TSR and survival in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC).Results: Nine cohort studies with 2031 patients with NSCLC were eligible for the meta-analysis. Pooled results showed that compared to those stroma-poor tumor, patients with stroma rich NSCLC were associated with worse recurrence-free survival (RFS, hazard ratio [HR] = 1.52, 95% confidence interval [CI]: 1.07 to 2.16, p = 0.02) and overall survival (OS, HR = 1.48, 95% CI: 1.20 to 1.82, p &lt; 0.001). Subgroup analyses showed that stroma-rich tumor may be associated with a worse survival of SCC (HR = 1.89 and 1.47 for PFS and OS), but a possibly favorable survival of AC (HR = 0.28 and 0.69 for PFS and OS). Results of meta-regression analysis also showed that higher proportion of patients with SCC was correlated with higher HRs for RFS (Coefficient = 0.012, p = 0.03) and OS (Coefficient = 0.014, p = 0.02) in the included patients, while higher proportion of patients with AC was correlated with lower HRs for RFS (Coefficient = −0.012, p = 0.03) and OS (Coefficient = −0.013, p = 0.04), respectively.Conclusion: Tumor TSR could be used as a predictor of survival in patients with NSCLC. The relative proportion of patients with SCC/AC in the included NSCLC patients may be an important determinant for the association between TSR and survival in NSCLC. Stroma richness may be a predictor of poor survival in patients with lung SCC, but a predictor of better survival in patients with lung AC.

<abstract> <p>Lowering the dose in single-photon emission computed tomography (SPECT) imaging to reduce the radiation damage to patients has become very significant. In SPECT imaging, lower radiation dose can be achieved by reducing the activity of administered radiotracer, which will lead to projection data with either sparse projection views or reduced photon counts per view. Direct reconstruction of sparse-view projection data may lead to severe ray artifacts in the reconstructed image. Many existing works use neural networks to synthesize the projection data of sparse-view to address the issue of ray artifacts. However, these methods rarely consider the sequence feature of projection data along projection view. This work is dedicated to developing a neural network architecture that accounts for the sequence feature of projection data at adjacent view angles. In this study, we propose a network architecture combining Long Short-Term Memory network (LSTM) and U-Net, dubbed LU-Net, to learn the mapping from sparse-view projection data to full-view data. In particular, the LSTM module in the proposed network architecture can learn the sequence feature of projection data at adjacent angles to synthesize the missing views in the sinogram. All projection data used in the numerical experiment are generated by the Monte Carlo simulation software SIMIND. We evenly sample the full-view sinogram and obtain the 1/2-, 1/3- and 1/4-view projection data, respectively, representing three different levels of view sparsity. We explore the performance of the proposed network architecture at the three simulated view levels. Finally, we employ the preconditioned alternating projection algorithm (PAPA) to reconstruct the synthesized projection data. Compared with U-Net and traditional iterative reconstruction method with total variation regularization as well as PAPA solver (TV-PAPA), the proposed network achieves significant improvement in both global and local quality metrics.</p> </abstract>