Aim: To evaluate the predictive power of tumor microRNA-210 (miR-210) on overall survival (OS) in glioma patients. Materials & methods: Studies were identified through searching PubMed, Embase and China National Knowledge Internet electronic databases. Meta-analyses were performed with a random- or fixed-effect model according to the heterogeneity. Results: Six studies were included. Results showed that increased miR-210 expression in tumor independently predicted poor OS in glioma patients (hazard ratio [HR]: 1.38; p = 0.001). Subgroup analyses showed that the prognostic efficacy of tumor miR-210 levels for OS was stronger in overall patients with glioma (HR: 2.22; p < 0.001) than in those with glioblastoma (HR: 1.13; p = 0.01). Conclusion: Expression of miR-210 may predict poor survival in patients with glioma.
To obtain sustainable
economical oil production and recovery of
investment, some oil fields adopted the strategy of multilayer commingling
production at an early stage. This leads to interlayer interference
and losing part of the recoverable reserves. In this paper, dynamic
interference behaviors of arbitrary multilayer commingling production
in heavy oil reservoirs are analyzed. Based on the non-Darcy flow
equation, the Buckly–Leverett equation, and the material balance
equation, a mathematical model of arbitrary multilayer commingling
production is obtained. Oil and water relative permeability, saturation,
and bottom hole flow pressure microelement and the iteration method
are employed to solve the mathematical model in the time domain. The
new model is verified by comparing the results from the typical black
oil model using the Darcy law. The sensitivity analysis of critical
parameters on interference behaviors, such as permeability, oil viscosity,
effective drainage boundary, and voidage replacement ratio, is carried
out. The model obtained in this paper can be used for oil and liquid
productivity analysis during the overall process of commingling production
and extended to be applied in numerical experiments with different
combinations of typical parameters as well.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.