Utilizing benchmarked dataset and gene regulatory network to investigate hub genes in postmenopausal osteoporosis

Objective: The objective of this paper was to investigate hub genes of postmenopausal osteoporosis (PO) utilizing benchmarked dataset and gene regulatory network (GRN). Materials and Methods: To achieve this goal, the first step was to benchmark the dataset downloaded from the ArrayExpress database by adding local noise and global noise. Second, differentially expressed genes (DEGs) between PO and normal controls were identified using the Linear Models for Microarray Data package based on benchmarked dataset. Third, five kinds of GRN inference methods, which comprised Zscore, GeneNet, context likelihood of relatedness (CLR) algorithm, Partial Correlation coefficient with Information Theory (PCIT), and GEne Network Inference with Ensemble of trees (Genie3), were described and evaluated by receiver operating characteristic (ROC) and precision and recall (PR) curves. Finally, GRN constructed according to the method with best performance was implemented to conduct topological centrality (closeness) for the purpose of investigate hub genes of PO. Results:A total of 236 DEGs were obtained based on benchmarked dataset of 20,554 genes. By assessing Zscore, GeneNet, CLR, PCIT, and Genie3 on the basis of ROC and PR curves, Genie3 had a clear advantage than others and was applied to construct the GRN which was composed of 236 nodes and 27,730 edges. Closeness centrality analysis of GRN was carried out, and we identified 14 hub genes (such as TTN, ACTA1, and MYBPC1) for PO. Conclusion: In conclusion, we have identified 14 hub genes (such as TN, ACTA1, and MYBPC1) based on benchmarked dataset and GRN. These genes might be potential biomarkers and give insights for diagnose and treatment of PO

Analysis of three family clusters of severe fever with thrombocytopenia syndrome by exposure risk matrix / 预防医学

Objective@#To analyze three events of severe fever with thrombocytopenia syndrome （SFTS） among family members by exposure risk matrix, so as to provide reference for SFTS prevention and control.@*Methods @#The field investigation and clinical data of seven confirmed cases with SFTS reported in Linhai from 2014 to 2016 were collected. Exposure risk matrix was used to list the risk of exposure two weeks before the onset, such as the environment, duration of activity and protection, and evaluate the possible routes of transmission. @*Results@#The first event involved three sisters. Two of them had plucked tea together on a hill, and the possibility of infection through tick bites were 60% and 75%, respectively. Another sister was more likely to be infected by ticks in her residence after visiting her sister （no physical contact with the sick sister）, with a possibility of 74%. The second event involved two cases （mother and son）. They were more likely to be infected by ticks in the current residential area, and the possibility were 100% and 80%, respectively. The third event involved two cases （husband and wife）. The wife had 60% possibility of being infected by the ticks on the hill she picked arbutus, and 40% by the ticks in her residence. The husband was most likely to be infected through contacting with body fluids or blood of his wife （44%）, then through the ticks on the hill he picked arbutus （33%）. @*Conclusion@#Among seven cases with SFTS reported in Linhai from 2014 to 2016, six cases have more than 50% possibility of being infected by tick bites; one case has higher possibility of being infected by contacting with body fluids or blood of a patient, but tick bites could not be ruled out.