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In recent years, breast cancer attracts more and more attention because of its high incidence. To explore the molecular functions and mechanisms, we performed RNA sequencing on the tumor tissues and their paired normal tissues from three breast cancer patients. By differential expression analysis, we found 3764 differentially expressed (DE) mRNAs, 5416 DE lncRNAs, and 148 DE circRNAs. Enrichment analysis suggested that the DE lncRNAs and DE circRNAs were enriched in mitochondria and nucleus, which indicated that they may participate in the vital metabolism directly or indirectly, such as fatty acid metabolism. Subsequently, the protein-protein interaction (PPI) network was constructed and we got 8 key proteins, of which the matrix metalloproteinase-9 (MMP9; degree 5) draws our attention. Based on the 38 up-regulated circRNAs and 14 down-regulated circRNAs, we constructed competing endogenous RNA (ceRNA) networks, from which the has-miR-6794-5p has been identified to enriched in the up-regulated network and correlated with the circNFIX directly. At this point, we presented that the circNFIX and MMP9 may play a significant role by regulating fatty acid metabolism in breast cancer. [ABSTRACT FROM AUTHOR]

This paper investigates the maximum genus and upper embeddability of connected 4-regular graphs. We obtain lower bounds on the maximum genus of connected 4-regular simple graphs and connected 4-regular graphs without loops in terms of the Betti number. The definition of the Betti number is referred to [Gross and Tucker, Topological Graph Theory, New York, 1987]. Furthermore, we give examples that show that these lower bounds are tight. [ABSTRACT FROM AUTHOR]

Background Two methods that are commonly used in most clinical trials for evaluating the effect of treatment on hot flashes are frequency only and severity score methods. However, in these crude methods, composite recurrent hot flash data on a patient are reduced to a one-dimensional summary measure, an approach which may not be optimal. In addition, the duration of a hot flash event provides additional information, which is not accounted for in the two methods mentioned above. Purpose We propose two new methods in the analysis of hot flash data in this paper. Methods The first method utilizes a generalization of the continuation ratio model to model the severity of a hot flash event. The model accounts for individual random effects and dependence of recurrent events within an individual. The other method that accounts for the duration of a hot flash event is a 3-Dimensional (3D) score method, which incorporates hot flash information on frequency, severity, and duration. Results Simulation studies were conducted to evaluate the properties of our proposed methods. The results indicate that our proposed generalized continuation ratio model has appreciably high power in detecting small treatment effects on severity compared with the two commonly used methods. The proposed 3D score, on the other hand, is sensitive in detecting treatment effects on both frequency and duration, but has low power in detecting treatment effects on severity alone. Conclusions Our proposed generalized continuation ratio model approach provides a valuable and powerful alternative to the two commonly used methods in the analysis of treatment effects on hot flash severity. Our proposed 3D score method incorporates the additional information hot flash duration provides, and is another analysis option for the practitioners to employ. [ABSTRACT FROM AUTHOR]

Simvastatin and fenofibrate are both commonly used lipid-regulating agents with distinct mechanisms of action, and their coadministration may be an attractive treatment for some patients with dyslipidemia. A 2-period, randomized, open-label, crossover study was conducted in 12 subjects to determine if fenofibrate and simvastatin are subject to a clinically relevant pharmacokinetic interaction at steady state. In treatment A, subjects received an 80-mg simvastatin tablet in the morning for 7 days. In treatment B, subjects received a 160-mg micronized fenofibrate capsule in the morning for 7 days, followed by a 160-mg micronized fenofibrate capsule dosed together with an 80-mg simvastatin tablet on days 8 to 14. Because food increases the bioavailability of fenofibrate, each dose was administered with food to maximize the exposure of fenofibric acid. The steady-state pharmacokinetics (AUC 0-24h, Cmax, andtmax) of active and total HMG-CoA reductase inhibitors, simvastatin acid, and simvastatin were determined following simvastatin administration with and without fenofibrate. Also, fenofibric acid steady-state pharmacokinetics were evaluated with and without simvastatin. The geometric mean ratios (GMRs) for AUC0-24h(80 mg simvastatin [SV] + 160 mg fenofibrate)/(80 mg simvastatin alone) and 90% confidence intervals (CIs) were 0.88 (0.80, 0.95) and 0.92 (0.82, 1.03) for active and total HMG-CoA reductase inhibitors. The GMRs and 90% CIs for fenofibric acid (80 mg SV + 160 mg fenofibrate/160 mg fenofibrate alone) AUC0-24hand Cmaxwere 0.95 (0.88, 1.04) and 0.89 (0.77, 1.02), respectively. Because both the active inhibitor and fenofibric acid AUC GMR 90% confidence intervals fell within the prespecified bounds of (0.70, 1.43), no clinically significant pharmacokinetic drug interaction between fenofibrate and simvastatin was concluded in humans. The coadministration of simvastatin and fenofibrate in this study was well tolerated. [ABSTRACT FROM AUTHOR]