Amir Ghaemi, Mohammad Fashbaf, Hoorie Soleimanjahi, Reza Omidbeigi, Taravat Bamdad, Davoud Hekmatpour, Kasra Hamdi,
Volume 10, Issue 2 (6-2007)
Abstract
Introduction: Nowadays, the attention of researchers has been focused on natural medicine in order to avoid the detrimental side effects of chemical drugs. In this study we assessed the effect of root extract of Tagetes minuta against HSV-1 and HSV-2. Materials and Methods: This research is an experimental study. Root extract of Tagetes minuta was obtained with 70% ethanol by maceration. Vero cells were grown in DMEM containing 5% fetal bovine serum. Serial dilutions of extracted suspension (1/10, 1/20, 1/40, 1/80, 1/160) were incubated by the exact titer of viruses and monitored for antiviral activity of extract. Data was analyzed using Doncan test. Results: Root extract obtained from Tagetes minuta significantly has antiviral activity against HSV-1 and HSV-2. This extract has more effect on HSV-2 than HSV-1. This study indicates that antiviral activity of the extract varies between different concentrations and the optimum antiviral activity on both viruses was obtained using 1/10 concentration. Conclusion:The results of this investigation showed that root extract of Tagetes minuta have good antiviral potenoial against HSV-1 and HSV-2, a good source of drug for treatment of diseases due to HSV-1 and HSV-2.
Azra Kenarkoohi, Hoorieh Soleimanjahi, Shahab Falahi, Hossein Riahi Madvar, S Zahra Meshkat,
Volume 13, Issue 4 (1-2011)
Abstract
Background: Based on the severity and prognostic condition of respective cancers caused by them, papilloma viruses are classified into high, medium, and low risk groups using E6 and E7 viral proteins. Nowadays, different methods of modeling in clinical medicine are used for diagnosis of diseases and evaluation of their molecular characteristics. Among the new methods of modeling, fuzzy systems are of particular importance in various fields of science. The aim of this study was to use a new intelligent Adaptive Nero Fuzzy Inference System (ANFIS) for predicting human papilloma virus oncogenicity based on a number of biochemical properties of E7 protein. Materials and Methods: In this study, using ANFIS model, a new model was developed for predicting oncogenicity of papilloma virus isolated from patients. The process of training and testing was performed using a set of available published filed data and several statistical and graphical criteria. Accordingly, through provision of needed biochemical and biophysical data on E7 gens from the existing data, this model was developed. The results of this model were, then, validated by the authentic published data. Results: Based on the results, the developed model is capable of predicting papilloma virus oncogenicity efficiently. R2 and RMSE values in training stage were 0.99 and 101.18, respectively. In the testing stage, however, they stood at 0.94 and 173.8, respectively. Conclusion: Based on the findings, the use of ANFIS model significantly improves the accuracy of estimating virus oncogenicity phenomenon. The methodology presented in this study is a new approach in estimating viral oncogenicity and can successfully be combined with other mathematical models for model updating in real conditions.
