ABSTRACT
Objective: Aggression is a disruptive behavior that limits children's ability for a better adjustment. As commonly reported, sleep problems is associated with the presentation of aggression in ADHD children. In this study, we aimed to investigate the association between sleep problems and aggressive behavior in children with ADHD
Methods: The study method is correlational and cross-sectional. The study population consists of children that were diagnosed with ADHD for the first time in Shiraz [south of Iran]. Fifty eight children [41 boys, 17 girls] clinically diagnosed with Attention Deficit-Hyperactivity Disorder, by a child and adolescence psychiatrist, participated in this study. They were enrolled by accessible sampling. Their ages ranged from 6 to 13 years [mean age=8.06 years, SD= 1.59]. None of The children were Medicaid recipients and participated in our study before beginning their medical treatment. Child Behavior Checklist [CBCL] and Children's Sleep Habits Questionnaire [CSHQ] were used for data collection. For data analysis descriptive statistics, significance tests, Pearson correlation coefficient, independent samples t-test and regression analyses, were used
Results: Children with ADHD showed a high prevalence of sleep problems, a significantly higher rate that reported before. Needing parent in room to sleep' [56.9%] was the most prevalent problem. With regard to Sleep habits, sleep duration was age-related [F=17.58, P<0.001]. Correlations between sleep problems and aggression were significant. Parasomnias wake-up time, daytime sleepiness and sleep duration were main predictors of aggressive behavior in children with ADHD and accounted for 56% of variance of aggression. No significant gender differences in sleep habits were observed
Conclusions: As aggressive behavior is a frequently reported problem in patients with ADHD, the results of the study may present a basis for effective diagnosis and treatment planning
ABSTRACT
Glioblastoma Multiforme [GBM] or grade IV astrocytoma is the most common and lethal adult malignant brain tumor. Several of the molecular alterations detected in gliomas may have diagnostic and/or prognostic implications. Proteomics has been widely applied in various areas of science, ranging from the deciphering of molecular pathogen nests of discuses. In this study proteins were extracted from the tumor and normal brain tissues and then the protein purity was evaluated by Bradford test and spectrophotometry. In this study, proteins were separated by 2-Dimensional Gel [2DG] electrophoresis method and the spots were then analyzed and compared using statistical data and specific software. Protein clustering analysis was performed on the list of proteins deemed significantly altered in glioblastoma tumors [t-test and one-way ANOVA; P< 0.05]. The 2D gel showed totally 876 spots. We reported, 172 spots were exhibited differently in expression level [fold > 2] for glioblastoma. On each analytical 2D gel, an average of 876 spots was observed. In this study, 188 spots exhibited up regulation of expression level, whereas the remaining 232 spots were decreased in glioblastoma tumor relative to normal tissue. Results demonstrate that functional clustering [up and down regulated] and Principal Component Analysis [PCA] has considerable merits in aiding the interpretation of proteomic data. 2D gel electrophoresis is the core of proteomics which permitted the separation of thousands of proteins. High resolution 2DE can resolve up to 5,000 proteins simultaneously. Using cluster analysis, we can also form groups of related variables, similar to what is practiced in factor analysis