Journal of Isfahan Medical School
Year:2019 | Volume:37 | Issue:558|Papers Count:3

Background: Due to the growing population of the elderly and the increasing trend of Alzheimer's disease, evaluation of acetylcholinesterase (AChE) and butyl cholinesterase (BChE) inhibitors, as major causes of Alzheimer's disease, is essential. Since the synthesis and investigation of each new compound is very costly and time-consuming, computational modeling techniques have been used to estimate biological activity. Up to now, various computational methods have been proposed which one of the major approaches, quantitative structure activity relationship, is based on the linear and non-linear methods using calculating the independent molecular descriptors. This study aimed to improve the biological activity prediction of AChE and BChE inhibitors using nonlinear random forest algorithm. Methods: In order to predict the biological activity of AChE and BChE compounds, linear partial least squares and nonlinear random forest algorithms were used. To obtain more accurate and reliable results, 80% of the compounds were randomly used as a training sample, and the rest as a test sample, to construct the model and evaluate the predictive power of the model. Findings: By applying nonlinear random forest model on AChE and BChE inhibitors, the accuracy of 89% was achieved. Finally, in order to examine more accurately the performance of the proposed model, the results were compared with the results obtained from the minimum partial error method, and the nonlinear random forest method had stronger performance than linear least squares method. Conclusion: The observations indicated that the nonlinear random forest method could be very effective in predicting the biological activity of AChE and BChE compounds proposed by physicians and pharmaceutical chemists. Therefore, before animal and human testing of the proposed compound, the biological activity of the compound was estimated approximately to be 90%. Based on the estimated biological activity, it can be argued that a new drug combination, at the expense of time and money, has the potential of becoming a new drug or not.

Background: The higher medical education system’ s mission is to maintain and improve the health in society. Furthermore, the roles of social determinants of health in health situation of society have been emphasized, and require in-depth and expansive studies. Therefore, the current study aimed to identify the position of social determinants of health in higher medical sciences education system. Methods: This study was conducted using qualitative approach with 20 experts in focus group discussion, and 8 experts in semi-structured interviews. The gathered information was reported using qualitative content analysis approach using codes, subcategories, and main categories. Findings: The findings of focus group discussion and semi-structured interviews with experts resulted in 500 codes, 17 subcategories, and 4 main categories of education, policymaking, legislation, and implementation, participation and accountability in public and private sectors, and weakness in areas related to social determinants of health. Conclusion: The findings of this study play a strategic role in medical education system for identification and expansion of social determinants of health. These findings can be used by policymakers, planners, and executives of education system to apply the teachings provided in medical education system, and create a more focused and productive system in the area of social determinants of health.

Background: Monoamine oxidase A (MAOA) enzyme activity is changed in mood disorders, as well as lower activity associated with criminal and aggressive behaviors. The MAOA gene, which plays a vital role in degradation of neurotransmitters such as serotonin, norepinephrine, and dopamine, contains a polymorphism in its promoter region that affects transcriptional efficiency. Moreover, MAOA-VNTR genotype has been related with both physical activity level and psychological measures. The aim of the current study was to determine the genetic variation and allelic frequency of the MAOA-VNTR in young population, and to compare the result with similar data from other populations. Methods: Salvia samples were obtained from 124 volunteers in Mashhad, Iran (age: 24. 3 ± 5. 7 years, 55 men and 67 women). DNA was extracted from the cheek cell, and the MAOA genotype was identified using polymerase chain reaction (PCR) with gene specific primers. The polymorphism was detected by PCR using primers: Forward: 5′ ACAGCCTGACCGTGGAGAAG-3′ and Revers: 5′ GAACGTGACGCTCCATTCGGA-3′ , and resulted in following products: 321 (3-repeat allele), 336 (3. 5-repeat allele), 351 (4-repeat allele), and 381 (5-repeat allele). Findings: From the sequencing results, 3. 5R, 4. 5R and 5. 5R repeats were successfully identified instead of the 3R, 4R, 5R repeats which were identified by previous researchers. The result of the MAOA-VNTR genotyping revealed that the three common genotype were 4. 5*4. 5, 3. 5*3. 5, and 3. 5*4. 5 with frequency of 46. 77%, 26. 61%, and 20. 96%, respectively, and the two common alleles were 4. 5R and 3. 5R with frequency of 37. 50% and 58. 06% respectively. The result of our study, compared with data of twelve populations, showed a significant difference between allele frequencies of Iranian samples with Iraqi, Afrikaner, New Zealand (European origin), German, Italian, Chinese and American populations (P < 0. 05). Conclusion: The frequency of MAOA allele is different between racial groups, and the frequency of the 4. 5R allele is greater in the men and women populations of our study. As a result, as previously confirmed, individuals with the 4. 5R allele have lower levels of physical activity, depression, and arousal due to high MAOA gene transcription activity.