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Articles by Mahmoud Mahmoudi
Total Records ( 2 ) for Mahmoud Mahmoudi
  Zohreh Amiri , Kazem Mohammad , Mahmoud Mahmoudi , Hojjat Zeraati and Akbar Fotouhi
  This study is designed to assess the application of neural networks in comparison to the Kaplan-Meier and Cox proportional hazards model in the survival analysis. Three hundred thirty gastric cancer patients admitted to and surgically treated were assessed and their post-surgical survival was determined. The observed baseline survival was determined with the three methods of Kaplan-Meier product limit estimator, Cox and the neural network and results were compared. Then the binary independent variables were entered into the model. Data were randomly divided into two groups of 165 each to test the models and assess the reproducibility. The Chi-square test and the multiple logistic model were used to ensure the groups were similar and the data was divided randomly. To compare subgroups, we used the log-rank test. In the next step, the probability of survival in different periods was computed based on the training group data using the Cox proportional hazards and a neural network and estimating Cox coefficient values and neural network weights (with 3 nodes in hidden layer). Results were used for predictions in the test group data and these predictions were compared using the Kaplan-Meier product limit estimator as the gold standard. Friedman and Kruskal-Wallis tests were used for comparisons as well. All statistical analyses were performed using SPSS version 11.5, Matlab version 7.2, Statistica version 6.0 and S_PLUS 2000. The significance level was considered 5% (α = 0.05). The three methods used showed no significance difference in base survival probabilities. Overall, there was no significant difference among the survival probabilities or the trend of changes in survival probabilities calculated with the three methods, but the 4 year (48th month) and 4.5 year (54th month) survival rates were significantly different with Cox compared to standard and estimated probabilities in the neural network (p<0.05). Kaplan-Meier and Cox showed almost similar results for the baseline survival probabilities, but results with the neural network were different: higher probabilities up to the 4th year, then comparable with the other two methods. Estimates from Cox proportional hazards and the neural network with three nodes in hidden layer were compared with the estimate from the Kaplan-Meier estimator as the gold standard. Neither comparison showed statistically significant differences. The standard error ratio of the two estimate groups by Cox and the neural network to Kaplan-Meier were no significant differences, it indicated that the neural network was more accurate. Although we do not suggest neural network methods to estimate the baseline survival probability, it seems these models is more accurately estimated as compared with the Cox proportional hazards, especially with today`s advanced computer sciences that allow complex calculations. These methods are preferable because they lack the limitations of conventional models and obviate the need for unnecessary assumptions including those related to the proportionality of hazards and linearity.
  Shahrzad Zamanai Taghizadeh Rabe , Mahmoud Mahmoudi , Ali Ahi and Seyed Ahmad Emami
  Objective: Different species of Artemisia (Asteraceae) have shown to exhibit antitumor activity. The aim of this study was to identify the antiproliferative effect of some Artemisia species from Iran on cultured human cancer cells. Materials and methods: Methanol, ethyl acetate, dichloromethane and n-hexane extracts from aerial parts of seven species of Artemisia were prepared and their antiproliferative effects on four cancer (AGS, HeLa, HT-29 and MCF-7) and normal cell line (L929) were determined. Different concentrations of extracts were added to cultured cells and incubated for 72 h. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay was employed to assess the cell viability. Results: Different extracts exert various growth inhibitory effects. In case of AGS cells, dichloromethane and methanol extracts of A. ciniformis Krasch. & Popov ex Poljak. (IC50 values: 35 and 60 μg/ml, respectively) showed the highest growth inhibitory effects. HeLa cells were more sensitive to both A. diffusa Krasch. ex Poljak. dichloromethane (IC50 value: 71 μg/ml) and A. ciniformis ethylacetate (IC50 value: 73 μg/ml) extracts. Dichloromethane extracts of A. diffusa, A. santolina Schrenk and A. ciniformis (IC50 values: 42, 91 and 94 μg/ml, respectively) exhibited more inhibition on HT-29 cells in comparison to other extracts. MCF-7 cells were best inhibited by A. ciniformis dichloromethane (IC50 value: 29 μg/ml) and A. vulgaris L. ethyl acetate (IC50 value: 57 μg/ml) extracts. Discussion and conclusion: This study shows the antiproliferative effects of Artemisia extracts on malignant cell lines. Artemisia could be also considered as a promising chemotherapeutic agent in cancer treatment.
 
 
 
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