PURPOSE: To determine impacts of psychological distress, gender role attitude, and housekeeping sharing on quality of life of gynecologic cancer survivors. METHODS: Subjects completed questionnaires consisting of four measurements: FACT-G (ver. 4) for quality of life, anxiety and depression from SCL-90-R for psychological distress, gender role attitude, and housekeeping sharing. A total of 158 completed data sets were analyzed by descriptive statistics, independent t-test, ANOVA, Pearson's correlation coefficient, and multiple regression analysis using SPSS 21.0 program. RESULTS: Quality of life was significantly and negatively correlated with psychological distress (r=−0.64, p < .001), but not with gender role attitude (r=−0.14, p=.820) or housekeeping sharing (r=0.08, p=.350). Psychological distress was significantly and positively correlated with gender role attitude (r=0.25, p < .010). Factors that significantly impacted quality of life were type of cancer (t=2.27, p=.025), number of treatment methods (t=2.58, p=.011), education level (t=3.33, p < .001), and psychological distress (t=−9.96, p < .001). CONCLUSION: Nursing interventions that can relieve psychological distress need to be developed for gynecologic cancer survivors. Nurses need to put priority on ovarian cancer survivors who have low education level with multiple treatment methods when performing nursing interventions to improve the quality of life of gynecologic cancer survivors.
Anxiety ; Dataset ; Depression ; Education ; Gender Identity* ; Housekeeping* ; Humans ; Nursing ; Ovarian Neoplasms ; Quality of Life* ; Survivors*

More effective production of human insulin is important, because insulin is the main medication that is used to treat multiple types of diabetes and because many people are suffering from diabetes. The current system of insulin production is based on recombinant DNA technology, and the expression vector is composed of a preproinsulin sequence that is a fused form of an artificial leader peptide and the native proinsulin. It has been reported that the sequence of the leader peptide affects the production of insulin. To analyze how the leader peptide affects the maturation of insulin structurally, we adapted several in silico simulations using 13 artificial proinsulin sequences. Three-dimensional structures of models were predicted and compared. Although their sequences had few differences, the predicted structures were somewhat different. The structures were refined by molecular dynamics simulation, and the energy of each model was estimated. Then, protein-protein docking between the models and trypsin was carried out to compare how efficiently the protease could access the cleavage sites of the proinsulin models. The results showed some concordance with experimental results that have been reported; so, we expect our analysis will be used to predict the optimized sequence of artificial proinsulin for more effective production.
Computer Simulation ; DNA, Recombinant ; Humans* ; Insulin ; Molecular Dynamics Simulation* ; Proinsulin ; Protein Sorting Signals ; Trypsin