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Shahlaei M.,Kermanshah University of Medical Sciences | Shahlaei M.,Isfahan University of Medical Sciences | Sabet R.,Isfahan University of Medical Sciences | Ziari M.B.,Islamic Azad University at Shahreza | And 4 more authors.
European Journal of Medicinal Chemistry | Year: 2010

Quantitative relationships between molecular structure and methionine aminopeptidase-2 inhibitory activity of a series of cytotoxic anthranilic acid sulfonamide derivatives were discovered. We have demonstrated the detailed application of two efficient nonlinear methods for evaluation of quantitative structure-activity relationships of the studied compounds. Components produced by principal component analysis as input of developed nonlinear models were used. The performance of the developed models namely PC-GRNN and PC-LS-SVM were tested by several validation methods. The resulted PC-LS-SVM model had a high statistical quality (R 2=0.91 and R CV 2=0.81) for predicting the cytotoxic activity of the compounds. Comparison between predictability of PC-GRNN and PC-LS-SVM indicates that later method has higher ability to predict the activity of the studied molecules. © 2010 Elsevier Masson SAS. All rights reserved.


Shahlaei M.,Kermanshah University of Medical Sciences | Shahlaei M.,Isfahan University of Medical Sciences | Madadkar-Sobhani A.,Barcelona Supercomputing Center | Saghaie L.,Isfahan University of Medical Sciences | And 3 more authors.
Expert Systems with Applications | Year: 2012

One strategy to potentially improve the success of drug design and development is to use chemometrics methods early in the process to propose molecules and scaffolds with ideal binding and to clarify physicochemical features influencing in their activity. Adaptive Neuro-Fuzzy Interference System (ANFIS) was used to construct the nonlinear quantitative structure-activity relationship (QSAR) model. The Genetic Algorithm (GA) was used to select descriptors which are responsible for the cathepsin K inhibitory activity of studied compounds. ANFIS regression is a nonlinear regression technique developed to relate many regressors to one or several response variables. The accuracy of the generated QSAR model (R 2 = 0.916) is described using various evaluation techniques, such as leave-one-out procedure (RLOO2=0.875) and validation through an external test set (Rpred2=0.932). © 2011 Elsevier Ltd. All rights reserved.


Saghaie L.,Isfahan University of Medical Sciences | Shahlaei M.,Isfahan University of Medical Sciences | Shahlaei M.,Kermanshah University of Medical Sciences | Fassihi A.,Isfahan University of Medical Sciences | And 4 more authors.
Chemical Biology and Drug Design | Year: 2011

Quantitative relationships between calculated molecular structure and 26 diaryl-substituted pyrazoles CCR2 inhibitors were investigated by GA-stepwise multiple linear regression. In multiple linear regression analysis, the quantitative structure-activity relationship models were constructed by grouping descriptors and also dual selection of variables using genetic algorithm and stepwise selection methods from each group of the pool of all calculated descriptors. The accuracy of the proposed multiple linear regression model was demonstrated using the following evaluation techniques: cross-validation, validation through an external test set, and Y-randomization. Furthermore, the domain of applicability that shows the area of reliable predictions was defined. The prediction results were in good agreement with the experimental values. © 2010 John Wiley & Sons A/S.


Saghaie L.,Isfahan University of Medical Sciences | Saghaie L.,Isfahan Pharmaceutical science Research Center | Shahlaei M.,Isfahan University of Medical Sciences | Shahlaei M.,Kermanshah University of Medical Sciences | And 3 more authors.
Journal of Molecular Graphics and Modelling | Year: 2010

The detailed application of multivariate image analysis (MIA) method for the evaluation of quantitative structure activity relationship (QSAR) of some cyclin dependent kinase 4 inhibitors is demonstrated. MIA is a type of data mining methods that is based on data sets obtained from 2D images. The purpose of this study is to construct a relationship between pixels of images of investigated compounds as independent and their bioactivities as a dependent variable. Partial least square (PLS) and principal components-radial basis function neural networks (PC-RBFNNs) were developed to obtain a statistical explanation of the activity of the molecules. The performance of developed models were tested by several validation methods such as external and internal tests and also criteria recommended by Tropsha and Roy. The resulted PLS model had a high statistical quality (R 2 = 0.991 and RCV2=0.993) for predicting the activity of the compounds. Because of high correlation between values of predicted and experimental activities, MIA-QSAR proved to be a highly predictive approach. © 2010 Elsevier Inc. All rights reserved.


Nokhodian Z.,Isfahan University of Medical Sciences | Yazdani M.R.,Isfahan University of Medical Sciences | Yaran M.,Isfahan University of Medical Sciences | Shoaei P.,Isfahan University of Medical Sciences | And 4 more authors.
Hepatitis Monthly | Year: 2012

Background: Female prisoners are at risk of acquiring sexually transmitted infections (STIs). There has been no previous study regarding the epidemiological status of STIs among female prisoners in Isfahan, central Iran. Objectives: The aim of this study was to investigate the prevalence and risk factors of the aforementioned infections among women incarcerated in the central prison, Isfahan, to determine appropriate prevention measures. Patients and Methods: In a cross-sectional study, all of the 163 women incarcerated in the central prison, Isfahan in 2009, were voluntarily enrolled by the census method. After completing a checklist consisting of demographic, social, and risk factors, a 5ml blood sample was taken from each individual. The sera were analyzed for markers of the hepatitis B virus (HBV; HBsAg, HBsAb, HBcAb), hepatitis C virus (HCV; HCV antibodies), human immunodeficiency virus (HIV; HIV antibodies), and syphilis (RPR). Confirmatory tests were performed on HCV antibody-positive cases. Results: The mean age of the participants in the study was 34.54 ± 11.2 years old, 94.3% of these women were Iranian, and many of them had only a primary level of education. The prevalence of HBsAg, HBcAb, HBsAb, and HCV antibodies were; 1.2%, 7.4%, 12.9% and 7.4% respectively. No positive RPR or HIV antibodies were detected. Conclusions: A significant relationship was seen between the HCV antibody, drug injection and illegal sex in the women, and also between HBc-Ab and drug injection. Regular screening, educational programs, and facilitation of access to suitable treatment care should be widely implemented in the prison population. Testing for immunity against HBV should be considered on admission, and afterwards vaccination of all prisoners and an appropriate preventative approach should be applied. © 2012 Kowsar Corp.


Sabet R.,Isfahan University of Medical Sciences | Mohammadpour M.,Isfahan University of Medical Sciences | Sadeghi A.,Isfahan University of Medical Sciences | Fassihi A.,Isfahan University of Medical Sciences | Fassihi A.,Isfahan Pharmaceutical science Research Center
European Journal of Medicinal Chemistry | Year: 2010

Quantitative structure activity relationships (QSAR) of anti-cancer isatin derivatives were discovered by multiple linear regressions (MLR) and genetic algorithm partial least squares (GA-PLS) methods. Topological, chemical, geometrical and functional groups descriptors were found to be effective parameters on the cytotoxic activity. The positive effects of the number of halogen atoms and the number of total secondary carbons, and the negative effects of the number of secondary amides, and the number of ketones on the anti-cancer activity were in agreement with previous SAR studies. Hansch analysis showed the importance of lipophilic R3 and R5 substituents. Between MLR and GA-PLS, MLR represented superior results with a high statistical quality (R2 = 0.92 and Q2 = 0.90) for predicting the activity of the compounds. © 2009 Elsevier Masson SAS. All rights reserved.


Razavi A.E.,Isfahan Pharmaceutical science Research Center | Ani M.,Isfahan Pharmaceutical science Research Center | Pourfarzam M.,Isfahan Pharmaceutical science Research Center | Naderi G.A.,Isfahan University of Medical Sciences
Journal of Research in Medical Sciences | Year: 2012

Background: High density lipoprotein (HDL) particles are heterogeneous in composition, structure, size, and may differ in conferring protection against cardiovascular disease. HDL associated enzyme, paraoxonase-1 (PON1), has an important role in attenuation of atherogenic low density lipoprotein (LDL) oxidation. The aim of this study was to investigate the associations between HDL particle size and PON1 activity in relation to serum HDL cholesterol (HDL-C) levels. Materials And Methods: One hundred and forty healthy subjects contributed to this study. HDL was separated by sequential ultracentrifugation and its size was estimated by dynamic light scattering. Paraoxonase activity was measured spectrophotometrically using paraoxon as substrate. Results: Results of this study showed that PON1 activity had negative correlations with HDL mean particle size (r = -0.22, P < 01), HDL2/HDL3 ratio, and serum HDL-C levels (r = -0.25, P < 0.01). HDL mean particle size and HDL2/HDL3 ratio had negative correlation with body mass index (BMI), waist hip ratio (WHR), and serum triglyceride (TG) levels, and positive correlation with serum HDL-C levels. Serum HDL-C levels had significant positive correlations with age, total cholesterol (TC), and apolipoprotein A-I (apo A-I) and significant negative correlation with BMI, WHR, and TG. Conclusion: Based on the results of this study, determination of HDL mean particle size beside the serum PON1 activity may help to better understand the CAD risks, pathogenesis, and prognosis, and may also help to design therapeutic protocols toward beneficial modifications of HDL characteristics.


Shahlaei M.,Isfahan University of Medical Sciences | Shahlaei M.,Kermanshah University of Medical Sciences | Fassihi A.,Isfahan University of Medical Sciences | Fassihi A.,Isfahan Pharmaceutical science Research Center | And 2 more authors.
European Journal of Medicinal Chemistry | Year: 2010

Principal component regression (PCR), principal component-artificial neural network (PC-ANN), and principal component-least squares-support vector machine (PC-LS-SVM) as regression methods were investigated for building quantitative structure-activity relationships for the prediction of inhibitory activity of some CCR1 antagonists. Nonlinear methods (PC-ANN and PC-LS-SVM) were better than the PCR method considerably in the goodness of fit and predictivity parameters and other criteria for evaluation of the proposed model. These results reflect a nonlinear relationship between the principal components obtained from molecular descriptors and the inhibitory activity of this set of molecules. The maximum variance in activity of the molecules, in PCR method was 45.5%, whereas nonlinear methods, PC-ANN and PC-LS-SVM, could explain more than 93.7% and 95.6% variance in activity data respectively. © 2010 Elsevier Masson SAS. All rights reserved.


Minaiyan M.,Isfahan University of Medical Sciences | Ghannadi A.,Isfahan University of Medical Sciences | Ghannadi A.,Isfahan Pharmaceutical science Research Center | Mahzouni P.,Isfahan University of Medical Sciences | Jaffari-Shirazi E.,Isfahan Pharmaceutical science Research Center
Iranian Journal of Pharmaceutical Research | Year: 2011

Antioxidant and immunomodulatory effects of anthocyanins are abundant in berberry fruits suggesting that they may have beneficial effects on inflammatory bowel diseases (IBD). The present study was carried out to investigate the anti-colitic effect of Berberis vulgaris fruit extract (BFE) compared to berberine chloride (BEC) and corticosteroids using an animal model of acetic acid induced experimental colitis. BFE with three different doses (375, 750, and 1500 mg/Kg) was administered orally or rectally prior to ulcer induction. BEC (10 mg/Kg), prednisolone (5 mg/Kg), hydrocortisone acetate enema (20 mg/Kg) and normal saline (5 mL/Kg) were considered as respective controls. The tissue was assessed macroscopically for damage scores, area, index and weight/length ratio. They were also examined histopathologically for inflammation extent and severity, crypt damage, invasion involvement and total colitis index. Results indicated that greater doses of oral BFE (750, 1500 mg/Kg) as well as BEC (10 mg/Kg) were effective to protect against colonic damage. By rectal pretreatment, the extract was only effective to diminish the ulcer index and the efficacy was not significant for mucosal inflammation parameters. In conclusion BFE, which is nearly devoid of berberine, was effective to protect against colitis and this might be attributed to its anthocyanin constituents. © 2011 by School of Pharmacy.


PubMed | Isfahan University of Medical Sciences and Isfahan Pharmaceutical science Research Center
Type: | Journal: Advanced biomedical research | Year: 2016

Hair growth as a key consumer objective has important role in the hair care products researches. This study was aimed to investigate the effect of a hair wax containing propolis, a resinous mixture produced by honeybees in The hair wax was designed and formulated compared with marketed brand hair wax and evaluated for pharmaceutical parameters including pH, homogeneity, consistency, spread ability, The selected hair wax formulation was stable and easy to wash. The formulation significantly increased hair length on 10The results of this study suggest that the formulated hair wax containing of propolis and

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