Background:Depression is a common medical condition with a high prevalence leading to emotional abnormality. Despite some drawbacks, depression currently diagnosed using a combination of patient interviews and self-report questionnaires. Recently, there is emerging emphasis to establish biomarkers to diagnosis and clinical management of depression. This case–control study was designed to develop microRNA (miRNA)-based serum biomarker for depression.Materials and Methods:In this study, 39 patients with depression and 36 healthy controls were enrolled. Serum miRNAs gene expression was measured using real-time polymerase chain reaction (PCR) analysis; finally, the data represent as the 2–ΔCt followed by further statistical analysis.Results:The serum level of miR-16 was significantly (P < 0.001) down-regulated (mean: 0.9123 and standard deviation [SD]: 0.06) in compared to normal individuals (mean: 1.6848 and SD: 0.09). The concentration of miR-135a was also catastrophically decreased (P < 0.001) in the patients (mean: 1.160 and SD: 0.07) in compared to control (mean: 1.819 and SD: 0.09). The relative miR-1202 expression levels were significantly lower (P < 0.001) in the patients (mean: 0.1755 and SD: 0.01) than in the healthy individuals (mean: 0.2939 and SD: 0.01). The receiver operating characteristic curve analysis indicated the obvious separation between patient and healthy control, with an AUC of 0.75 (95% confidence interval [CI] = 0.642–0.858, P < 0.001), 0.72 (95% CI = 0.607–0.834, P < 0.001), and 0.74 (95% CI = 0.630–0.861, P < 0.001) for miR-16, miR-135a, and miR-1202, respectively. The data suggest that these miRNAs have a potential to be used as a biomarker of depression with sensitivity 77.8% and specificity of 61.5% for miR-16, 94.4% and 41.0% for miR-135a as well as 86.1% and 61.5% for miR-1202, respectively (P < 0.001).Conclusion:Our findings showed that these miRNA can be used as a biomarker of depression diagnosis. MiR-135a and miR-1202 exhibited better sensitivity and specificity, respectively.

This study reviewed the effect of instructing cognitive and metacognitive strategies on the academic progress of Medical Sciences of Ilam University students. The research is quasi-experimental including a pre-test and a post-test. The population of the research includes the students of Medical Sciences of Ilam University. The sample includes 120 students selected using multi-stage random sampling method from four majors of nursing, occupational health, family health and medicine. All the participants had passed at least two semesters. The participants participated in six cognitive and metacognitive strategies classes held by the researcher. The data were analyzed using descriptive and inferential statistical methods (independent and dependent t-tests) and variance analysis using SPSS (statistical package for the social sciences) (version 13) software. The results showed that instructing cognitive and metacognitive strategies positively affected students' academic progress and proved to be an effective learning method. The average of GPAs (general point averages) of experimental and control groups were significantly different. Instructing the strategies was significantly different across majors and genders.

No abstract