PurposeInsufficient sensitivity and specificity prevent the use of most existing biomarkers for early detection of breast cancer. Recently, it was reported that serum microRNAs (miRNAs) may be potential biomarkers in many cancer diseases. In this study, we investigated whether serum levels of 5 miRNAs including miR-21, miR-125b, miR-145, miR-155, and miR-365 could discriminate breast cancer patients and healthy controls.MethodsSerum levels of miRNAs were measured by using quantitative real-time polymerase chain reaction in 99 breast cancer patients and 21 healthy controls. The abundance change of serum miRNAs were also evaluated following surgical resection in 20 breast cancer patients. Receiver operating characteristic (ROC) curve analysis was performed to assess the sensitivity and specificity of miRNAs as diagnostic biomarkers.ResultsSerum levels of miR-21 and miR-155 was significantly higher, while miR-365 was significantly lower in breast cancer as compared with healthy controls. The serum levels of miR-21 and miR-155 significantly decreased following surgical resection. Additionally, the serum level of miR-155 at stages I and II was significantly higher compared to stage III. The serum miR-145 level was remarkably higher in progesterone receptor (PR)-positive patients than PR-negative. The positivity of miR-21, miR-155, and miR-365 was high compared to CA 153 and CEA in breast cancer. ROC curve analyses of a combination of miR-21, miR-155, and miR-365 yielded much higher area under curve and enhanced sensitivity and specificity in comparison to each miRNA alone.ConclusionThe combination of serum miR-21/miR-155/miR-365 may potentially serve as a sensitive and specific biomarker that enables differentiation of breast cancer from healthy controls.

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In this paper we study how to trade off the economic and ecological effects in the remanufacturing closed-loop logistics network design in the context of low-carbon economy. We establish a multi-objective mixed integer linear programming model to find the optimal facility locations and materials flow allocation. In the objective function, we set three minimum targets: economic cost, CO2 emission and waste generation. Through an iterative algorithm, we get the Pareto Frontier of our problem. In the numeric study, we find that in order to achieve a Pareto improvement over an original system, three of the critical rates (i.e. return rate, recovery rate, and cost substitute rate) should be increased. Also, to meet the need of low-carbon dioxide, we plot an iso-CO2 emission curve in which decision makers have a series of optimal choices with the same CO2 emission but different cost and waste generation. Each choice may have different network design but all of these are Pareto optimal solutions, which provide a comprehensive evaluation of both economics and ecology for the decision making.

In order to obtain the heterogeneity of coal, the mechanical tests were performed. The experimental results show that the heterogeneity of the mechanical parameters for coal follow the Weibull distribution. Then the model of coupled gas flow and deformation process for heterogeneous coal was presented and the effects of heterogeneity of coal on gas flow and failure of coal were investigated. The finding is that the effect of the heterogeneity of coal on gas flow and mechanical failure of coal can be considered by the model in this paper. Failure of coal has a great effect on gas flow.