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Fangdong Jiao, Hao Sun, Qingya Yang, Hui Sun, Zehua Wang, Ming Liu, Jun Chen Department of Urology, Shandong University Qilu Hospital (Qingdao), Qingdao, People’s Republic of ChinaCorrespondence: Jun ChenDepartment of Urology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, 758 Hefei Road, Qingdao, Shandong 266035, China Tel +86 18561810509Fax +86 532-66850532Email qlyychenjun@163.comPurpose: Aim of this study was to identify biomarkers between different grades of bladder cancer (BLCA) and its prognostic value.Methods: mRNA expression data from GSE32549 and GSE71576 were extracted for further analysis. Differentially expressed genes (DEGs) were identified using GEO2R web tool. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein–protein interaction (PPI) network were conducted to explore the function and relationship of DEGs. The Cancer Genome Atlas (TCGA) database was used for external validation and Gene set enrichment analysis (GSEA) analysis was used to further identify FADS1 pathways. Bladder cancer cells and patient specimens were used to further demonstrate the function of FADS1.Results: Datasets from GEO identified a panel of DEGs. Functional enrichment analysis highlighted that DEGs were associated with nuclear division, spindle, cell cycle and p53 signaling pathway. External validation from TCGA demonstrated that FADS1 was an independent prognostic marker in BLCA patients. In cell lines and tumor specimen analysis, FADS1 was overexpressed in the tumor specimen, compared with adjacent tissues, and positively correlated with tumor grade of BLCA. Moreover, FADS1 could enhance the proliferation ability and influence cell cycle of bladder cancer cells.Conclusion: FADS1 was an independent prognostic biomarker for BLCA and could confer the bladder cancer cells increased proliferation ability.Keywords: FADS1, bioinformatics, bladder cancer, TCGA, proliferation

Purpose Aim of this study was to identify biomarkers between different grades of bladder cancer (BLCA) and its prognostic value. Methods mRNA expression data from GSE32549 and GSE71576 were extracted for further analysis. Differentially expressed genes (DEGs) were identified using GEO2R web tool. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and protein-protein interaction (PPI) network were conducted to explore the function and relationship of DEGs. The Cancer Genome Atlas (TCGA) database was used for external validation and Gene set enrichment analysis (GSEA) analysis was used to further identify FADS1 pathways. Bladder cancer cells and patient specimens were used to further demonstrate the function of FADS1. Results Datasets from GEO identified a panel of DEGs. Functional enrichment analysis highlighted that DEGs were associated with nuclear division, spindle, cell cycle and p53 signaling pathway. External validation from TCGA demonstrated that FADS1 was an independent prognostic marker in BLCA patients. In cell lines and tumor specimen analysis, FADS1 was overexpressed in the tumor specimen, compared with adjacent tissues, and positively correlated with tumor grade of BLCA. Moreover, FADS1 could enhance the proliferation ability and influence cell cycle of bladder cancer cells. Conclusion FADS1 was an independent prognostic biomarker for BLCA and could confer the bladder cancer cells increased proliferation ability.

Early-stage encrypted traffic classification refers to the identification of the application to which the flow belongs within a limited number of transmission packets or bytes after the network flow is connected and before the end of the data transfer cycle. Accurate identification is an important foundation for quality of service (QoS), network management, policy-based routing, and traffic accounting. With the widespread use of common encryption protocols such as Transport Layer Security Protocol (TLS) and Quick UDP Internet Connection (QUIC), traffic is showing a trend of being fully encrypted, in addition, the large-scale traffic in the mobile core network, traffic asymmetry, packet loss and disorder caused by complex network topology present enormous challenges to the early-stage classification of mobile application traffic. In this paper, we propose a highly robust early-stage classification fingerprint generation method for encrypted mobile traffic named SpBiSeq (Simple Bi-Directional Sequence), which has better classification performance, better anti packet loss ability than previous studies. Furthermore, SpBiSeq has low time and space complexity, which makes it well adapted to high-speed network environments.

Background The amplification of gene COPS3 is closely related to the development of osteosarcoma and hepatocellular carcinoma. However, the effects of COPS3 on prostate cancer (PCa) are poorly understood. Methods In this study, the protein expression of COPS3 in PCa tissues, adjacent normal tissues, and bone metastasis tissues of PCa was analyzed by immunohistochemistry. Furthermore, cell proliferation, colony formation, migration, and invasion assay were performed in 22rv1 and PC-3 cells after knocking down COPS3 by small interfering RNAs. Furthermore, we performed western blot analysis to explore the potential mechanisms underlying it. Results This study found that the overall survival of the COPS3 high-expression group was significantly shorter than the low-expression group. This study discovered that the protein expression of COPS3 in PCa tissues was higher than that in the matched nontumor prostate tissues. In addition, tissues from bone metastasis of PCa had a high percentage of overexpressing COPS3. After knockdown of the COPS3 gene in 22rv1 and PC3 cells, two classic human PCa cell lines which had a high level of COPS3, the abilities of migration, invasion, and proliferation were inhibited. Finally, protein levels of phosphorylated P38 mitogen-activated protein kinase (MAPK) and N-cadherin were significantly decreased after knocking down the expression of COPS3, and the protein levels of E-cadherin were significantly increased. Conclusions In conclusion, COPS3 may be closely related to the progress of PCa. Knockdown of COPS3 inhibited the progress of PCa through reducing the levels of phosphorylated P38 MAPK and impaired the epithelial-mesenchymal transition process.

Background: Mesenchymal stem cells (MSCs) have been proved to be able to differentiate into cells that are conducive to tumor growth and invasion. The mechanism is not clear. This present study was aimed to find out whether TGFβ1-Smad pathway was involved in this process. Methods: For the in vitro experiment, five groups of MSCs were cultured to test whether VX2 culture supernatant could induce the differentiation of MSCs into myofibroblasts. And then transforming growth factor β1(TGFβ1) receptor or Smad2 of MSCs were blocked by RNA interference technique to test whether TGFβ1-Smad pathway was involved in the differentiation. In the animal experiment, different kinds of MSCs were co-inoculated with VX2 cells in bladder to test whether the blockage of TGFβ1 receptor or Smad2 of MSCs could affect the expression of TGFβ1, epidermal growth factor (EGF), fibroblast activation protein alpha (FAPa), and matrix metalloprotein 9 (MMP9) in five animal groups. Results: VX2 culture supernatant could up-regulate the expression of α-SMA and Vimentin in MSCs, which indicated that VX2 culture supernatant could induce the differentiation of MSCs into myofibroblasts. Either the Blockage of TGFβ1 receptor or Smad2 of MSCs could lead to decreased expression of α-SMA and Vimentin in MSCs. In the animal experiment, MSCs could favor VX2 bladder tumor growth and up-regulate the expression of TGFβ1, EGF, FAPa, MMP9 in VX2 tumor tissue. However, when TGFβ1 receptor or Smad2 of MSCs was blocked, the above effects were attenuated. Conclusions: Under the induction of tumor microenvironment, MSCs can differentiate into myofibroblasts and then affect tumor interstitial microenvironment remodeling. This process is mediated by TGFβ1-Smad2 pathway.

Objective To analyze the risk factors of patients with diabetes mellitus (DM) and urosepsis after percutaneous nephrolithotomy (PCNL) for upper urinary tract stones and to develop a nomogram to predict postoperative urosepsis according to the risk factors. Methods The data of patients with type 2 diabetes who underwent one-stage PCNL due to upper urinary tract stones were retrospectively analyzed. The risk factors of patients with postoperative urosepsis were evaluated by univariate and multivariate logistic regression analysis, and the nomogram prediction model was developed according to the regression coefficient. Results One-stage PCNL was successfully completed in 241 patients with DM, and urosepsis occurred in 41 (17.0%) patients after PCNL. Based on multivariate logistic regression analysis, the independent risk factors associated with postoperative urosepsis included preoperative leukocyte elevation (OR = 3.973, P = 0.005), positive urine nitrite (OR = 3.697, P = 0.010), and positive urine culture (OR = 3.562, P = 0.002). According to the results of the logistic regression analysis model, staghorn stones (OR = 2.049, P 0.05. Conclusion Preoperative leukocyte elevation, positive urine nitrite, and positive urine culture are independent risk factors for urosepsis after one-stage PCNL for patients with DM with upper urinary tract stones. The nomogram, which is based on independent risk factors that combine stone morphology and intraoperative stone clearance, can help predict the risk of postoperative urosepsis.

Proxies can provide privacy and anonymity protection for users, but can also be exploited by attackers to hide their malicious behaviors. In order to strengthen the monitoring and management of network, proxy detection has become an urgent and challenging task. Although a great deal of efforts has been made for proxy detection, existing methods mostly rely on the packet-level features of a single flow, such as packet inter-arrival time and payload size. In addition, handling the raw traffic throughout the communication process may lead to user privacy leakage to a certain extent. Considering the use of multi-flow statistics and reducing the invasion of user privacy, in this paper, we propose a machine learning based approach for proxy detection with NetFlow data, which only contains session-level statistical information. We extract features through NetFlow data aggregation to build machine learning model and verify the performances on different combinations of features to get the optimal feature sets. Furthermore, the importance of appropriate time windows and minimum flow numbers of NetFlow data aggregation are demonstrated by comprehensive experiments. Based on the real-world datasets, our detection method can distinguish proxy and normal traffic accurately, and achieve about 96% True Positive Rate(TPR) in our experiments with random forest classifier.

Available bandwidth(ABW) has become a key indicator of network measurement, in order to measuring measurement accuracy, in particular, the measurement speed with available bandwidth measurement is also very important. This paper proposes a quick available bandwidth method named QuickAbw, which obtains the available bandwidth quickly under the two link delay growth rates. The link delay growth rate is the rate of growth in the interval between probe packets over time when low-intrusion probe packets with equal intervals just cause link congestion. It is worth mentioning that the probe packets stop sending immediately after causing the link node to overflow, so this method has little impact on the link. Simulations show that QuickAbw has higher measurement accuracy and shorter measurement time than other well-known available bandwidth tools for comparison in a network with single bottleneck-link. Finally, we tested in a real environment consistent with the simulation environment settings, and the experimental results were basically consistent with the simulation results.

Clear cell renal cell carcinoma (ccRCC) is one of the most commonly diagnosed kidney tumors and is often accompanied by immune cell infiltration. In this study, we attempted to identify microenvironment-associated genes and explore the correlation between CXCL13 and tumor-infiltrating immune cells (TIICs). Gene expression profiles and their corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. The ESTIMATE (Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data) algorithm was used to calculate immune cell and stromal cell scores, according to which patients were divided into high- and low-score groups, allowing differentially expressed genes (DEGs) to be identified. Functional enrichment and PPI network analysis were used to identify the functions of the DEGs. CIBERSORT algorithm and TIMER analysis were used to evaluate the immune score. Oncomine and TCGA database were used to explore CXCL13 mRNA expression level in ccRCC. High ESTIMATE score was significantly associated with prognosis. Functional enrichment analysis clarified that DEGs were associated with T cell activation, immune response-regulating cell surface receptor signaling pathway, and positive regulation of cytokine production. PPI network was used to identify CXCL13 as a hub gene. And CIBERSORT algorithm and TIMER analysis showed that strong correlation between CXCL13 expression level and TIICs. Oncomine database was used to validate high CXCL13 expression level in ccRCC tissue, compared to normal tissues. In conclusion, we obtained a list of tumor microenvironment-related genes and identified CXCL13 as an immune response biomarker in patients with ccRCC, GSEA analysis, wound healing and transwell assays showed CXCL13 played a role in tumor migration.

With the increasing attention on communication security, Virtual private network(VPN) technology is widely used to meet different security requirements. VPN traffic detection and classification have become an increasingly important and practical task in network security management. Although a lot of efforts have been made for VPN detection, existing methods mostly extract or learn features from the raw traffic manually. Manual-designed features are often complicated, costly, and time-consuming. And, handling the raw traffic throughout the communication process may lead to the compromise of user privacy. In this paper, we apply bidirectional LSTM network with attention mechanism to the VPN traffic detection problem and propose a model named NetFlow Sequence Attention Network (NSA-Net). The NSA-Net model learns representative features from the NetFlow sequences rather than the raw traffic to ensure the user privacy. Moreover, we adopt the attention mechanism, which can automatically focus on the information that has a decisive effect on detection. We verify our NSA-Net model on the NetFlow data generated from the public ISCXVPN2016 traffic dataset. And the experiment results indicate that our model can detect VPN from non-VPN traffic accurately, and achieve about 98.7% TPR. Furthermore, we analyze the performance of our model in the presence of sampling and our model still achieves over 90% TPR and Accuracy at low sampling rates.

Owing to the fragile kidney and relative small collecting system of pediatric patients, urologists were always reluctant to treat pediatric urolithiasis with PCNL. Here we conduct a study to assess the effectiveness and safety of pediatric patients with renal calculi

To compare the efficacy between total ureterectomy and partial ureterectomy in treatment of ureteral carcinoma.The clinical data and follow-up results of 102 patients with ureteral urothelial carcinoma from August 1996 to August 2011 were analyzed retrospectively. According to surgical procedures, the patients were divided into total ureterectomy group (61 cases) and partial ureterectomy group (41 cases). The subsequent bladder cancer incidence, ureteral carcinoma recurrence rate, distant metastasis rate and survival rate were compared between two groups. The prognostic factors of ureteral carcinoma were analyzed by multivariable Cox regression.Nineteen patients (31.1%) suffered subsequent bladder cancer in total ureterectomy group, and 10 (24.4%) in partial ureterectomy group(χ² = 0.550, P = 0.458). Ten patients (16.4%) re-suffered contralateral ureteral carcinoma in total ureterectomy group, and 6 (14.6%) in partial ureterectomy group, 2 (4.9%) ipsilateral and 4 (9.7%) contralateral (χ² = 0.057, P = 0.811). Eight patients (13.1%) occurred distant metastasis in total ureterectomy group, and 3 (7.3%) in partial ureterectomy group (χ² = 0.360, P = 0.549). Twenty patients died of carcinoma in total ureterectomy group, and 18 in partial ureterectomy group. The median survival time was 78 months in total ureterectomy group, and 75 months in partial ureterectomy group. The 1-year, 3-year and 5-year survival rates in total ureterectomy group were 97.8%, 76.8% and 63.6%, and in partial ureterectomy group were 93.0%, 66.9% and 58.8%. The multivariable Cox regression analysis revealed that tumor stage (RR = 2.468, P = 0.009) and local lymph node status (RR = 3.081, P = 0.020) were independent prognostic factors of ureteral carcinoma. The 5-year survival rate of Ta-2 stage tumor was 73.4%, and of T3-4 stage was 42.8%.Tumor stage and local lymph node status are key prognostic factors of ureteral carcinoma. The efficacy between total ureterectomy and partial ureterectomy in treating early stage of low ureteral carcinoma is similar. Partial ureterectomy can be used in selective patients.