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ObjectiveTo explore dynamic changes of cytokines and virological markers associated with hepatitis B surface antigen (HBsAg) loss during peginterferon alpha-2a (PEG-IFN α-2a) treatment in hepatitis B e antigen (HBeAg) positive chronic hepatitis B (CHB) patients.MethodsIt was a single-center prospective cohort study. HBeAg-positive CHB patients were prospectively and consecutively enrolled. Cytokines were detected at baseline, week 12 and 24 of PEG-IFN treatment. HBsAg disappearance rate was the primary evaluation index at 48 weeks of PEG-IFN treatment.ResultsAmong 100 patients who completed the 48-week PEG-IFN α-2a treatment, 38 patients achieved serum HBeAg disappearance, 25 patients achieved HBeAg seroconversion, 9 patients achieved functional cure, 37 patients had HBsAg decline of ≥1 log IU/ml, and 8 patients produced hepatitis B surface antibody (HBsAb). Albumin (ALB), fms-like tyrosine kinase 3 ligand (FLT3-L) and interferon-alpha2 (IFN-α2) in the clinical cure group were significantly lower than those in the non-clinical-cure group at baseline. After 12 weeks of treatment, HBsAg in the clinical cure group was significantly lower than that in the non-clinical-cure group (median 1.14 vs. 3.45 log10IU/ml, Z=-4.355, P < 0.001). The decrease of HBsAg and hepatitis B virus desoxyribose nucleic acid (HBV DNA) in the clinical cure group was significantly higher than that in non-clinical-cure group (median: HBsAg 1.96 vs. 0.33 log10IU/ml, Z=-4.703, P< 0.001; HBV DNA 4.49 vs.3.13 log10IU/ml, Z=-3.053, P=0.002). The increase of IFN-α2 in the cure group was significantly higher than that in the non-clinical-cure group (497.89 vs. 344.74, Z=-2.126, P=0.034). After 24 weeks of treatment, HBsAg, HBeAg, Flt3-L, and IL-10 in the clinical cure group were significantly lower than those in the non-clinical-cure group (median: HBsAg 0.70 vs. 3.15 log10IU/ml, Z=-4.535, P< 0.001; HBeAg 1.48 vs. 13.72 S/CO, Z = 2.512, P = 0.012; Flt3-l 0.00 vs 2.24 pg/ml, Z = 3.137, P=0.002; IL-10 0.70 vs. 2.71 pg/ml, Z=-4.067, P < 0.001). HBsAg decreased significantly in the clinical cure group compared with non-clinical-cure group (median 3.27 vs. 0.45, Z=-4.463, P < 0.001).ConclusionDynamic changes of cytokines and virology markers during early PEG IFN α-2a treatment were associated with HBsAg loss in HBeAg-positive CHB patients.

Background To identify pivotal lncRNAs in papillary thyroid cancer (PTC) using lncRNA–mRNA–miRNA ceRNA network analysis. Methods We obtained gene expression profiles from the gene expression omnibus database. Cancer specific lncRNA, cancer specific miRNA and cancer specific mRNA were identified. An integrated analysis was conducted to detect potential lncRNA–miRNA–mRNA ceRNA in regulating disease transformation. The lncRNA regulated gene ontology (GO) terms and regulated pathways were performed by function analysis. Survival analysis was performed for the pivotal lncRNAs. Results A total of four lncRNAs, 15 miRNAs and 375 mRNAs are identified as the key mediators in the pathophysiological processes of PTC. GO annotation enrichment analysis showed the most relevant GO terms are signal transduction, integral component of membrane and calcium ion binding. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed different changed genes mainly enriched in pathways in cancer, PI3K-Akt signaling pathway and focal adhesion. Among four lncRNAs, only SLC26A4-AS1 was significantly associated with PTC patient disease free survival. Conclusion This study has constructed lncRNA–mRNA–miRNA ceRNA networks in PTC. The study provides a set of pivotal lncRNAs for future investigation into the molecular mechanisms.

With the increasing development of cloud computing,task scheduling problem become a crucial aspect.There are many scholars research on resource scheduling problems,but load balancing and scheduling in how to balance time and cost is still not achieved satisfactory results.Genetic algorithm(GA) has strong robustness and inherent parallel computer system,particularly suitable for the combinatorial optimization problems, but the basic genetic algorithm easy to fall into local optimal solution. So ,we propose a crossover-mutation operator in mutation to solve this problem. The performance is analyzed using Cloudsim simulator and compared with existing GA ,Min-min algorithm. Simulation results demonstrate that the proposed algorithm has better performance in load balancing ,finish time and costs.

Diagnostic tests are central in the field of modern medicine. One of the main factors for interpreting a diagnostic test is the discriminatory accuracy. For a continuous-scale diagnostic test, the area under the receiver operating characteristic (ROC) curve, AUC, is a useful one-number summary index for the diagnostic accuracy of the test. When only a particular region of the ROC curve would be of interest, the partial AUC (pAUC) is a more appropriate index for the diagnostic accuracy. In this thesis, we develop seven confidence intervals for the pAUC under the semi-parametric models for the diseased and non-diseased populations by using the normal approximation, bootstrap and empirical likelihood methods. In addition, we conduct simulation studies to compare the finite sample performance of the proposed confidence intervals for the pAUC. A real example is also used to illustrate the application of the recommended intervals.