Background Cervical cancer is the second leading cause of death in women 20–39 years old. Because coverage for cervical cancer screening is low, and the vaccination rate of human papillomavirus (HPV) is poor in some countries, potential markers to detect the disease at early stages are needed. E2F transcription factors (E2Fs) are a family of transcription factors that function in cell proliferation, differentiation, apoptosis, and tumorigenesis. As abnormal activation and regulation of E2Fs are related to tumor development and poor prognosis, we performed bioinformatic analyses and in vitro assays to evaluate the role of E2Fs in cervical cancer. Methods Transcriptional expression of E2Fs was initially evaluated in silico using ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA), followed by evaluation of E2F1/2/7/8 protein levels using immunohistochemistry in 88 patient tissues. E2F2 and E2F7 mRNA levels were measured by RT-qPCR. LinkedOmics and Metascape were used to predict functions of E2Fs, and in vitro experiments were performed to assess the tumorigenic role of E2F2 and E2F7. Results In silico analysis showed that E2F1/2/7/8 were significantly overexpressed in cervical cancer, findings which were confirmed at the protein level using immunohistochemistry. Further, upregulation of E2F1/2/7/8 was associated with different clinicopathological prognostic factors, including positivity for lymph vessel invasion and deep invasion of cervical stroma. Increased expression of E2F1/2/7/8 was also related to shorter overall survival (OS) and disease-free survival (DFS) in patients with cervical cancer. Using multivariate analysis, we confirmed E2F1/2/7/8 as independent prognostic factors for shorter OS of patients with cervical cancer. Finally, in vitro experiments showed that E2F2 and E2F7 are involved in cell proliferation and migration and cell cycle regulation in both HPV-positive and HPV-negative cervical cancer cells. Conclusions E2F1/2/7/8 may be prognostic biomarkers for survival of patients with cervical cancer. E2F2 and E2F7 are involved in cell proliferation, migration, and cell cycle in both HPV-positive and HPV-negative cervical cancer cells.

The quality of rural residential building products related to the construction pace of new socialist countryside in China. In order to improve the products quality, the optimum index of target analysis is used here. Analyzed and established the evaluation hierarchical model for the rural residential building products, using the optimum index of target analysis to evaluate the quality of the product, the concrete steps is given with the examples, obtained the quantify the quality of evaluation value. Compared with the other evaluation methods, the evaluation of the optimum index of target analysis has the feature of Intuitive, simple, quantitative, precise, and has greater application value.

In order to improve network reliability and stability of the core layer, multiple devices are connected together through the IRF physical port, IRF (Intelligent Resilient Framework) configuration, virtual into “virtual equipment”. Using the virtualization technology can set the equipment resources of the hardware and software processing capability, collaborative work, the equipment management and the uninterrupted maintenance. Through introduce the basic concepts and working principles of H3C Switches IRF system, also analyzes the typical applications of IRF technology in network system.

The quality of rural residential building products related to the construction pace of new socialist countryside in China. In order to improve the products quality, using the rough set theory, hierarchy evaluation model is established and analyzed. The step of the rural residential building products quality evaluation is given combined with an instance, and the quality evaluation value is also given quantitatively. The result shows that this method is intuitional, concise, quantitative and precise thereby it has the great merit of being applied widely.

Nowadays, there are lots of internet-based service platforms about construction products. The building products’ types are too many to select. This paper proposes an algorithm applying user-based collaborative filtering method to building products selection, which implements personalized recommendation with the help of group users’ experience. The algorithm provides decision support to relevant personnel and improves the efficiency and quality of building products selection.