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    Inhibitory activity on type 2 diabetes and hypertension key-enzymes, and antioxidant capacity of veronica persica phenolic-rich extracts

    , Article Cellular and Molecular Biology ; Volume 62, Issue 6 , 2016 , Pages 80-85 ; 01455680 (ISSN) Sharifi Rad, M ; Tayeboon, G. S ; Sharifi Rad, J ; Iriti, M ; Varoni, E. M ; Razazi, S ; Sharif University of Technology
    Cellular and Molecular Biology Association  2016
    Veronica genus (Plantaginaceae) is broadly distributed in different habitats. In this study, the inhibitory activity of free soluble and conjugated phenolic extracts of Veronica persica on key enzymes associated to type 2 diabetes (α-glucosidase and α-amylase) and hypertension (angiotensin I converting enzyme, ACE) was assessed, as well as their antioxidant power. Our results showed that both the extracts inhibited α-amylase, α-glucosidase and ACE in a dose-dependent manner. In particular, free phenolic extract significantly (P < 0.05) inhibited α-glucosidase (IC50 532.97 μg/mL), whereas conjugated phenolic extract significantly (P < 0.05) inhibited a-amylase (IC50 489.73 μg/mL) and ACE... 

    QSAR study of heparanase inhibitors activity using artificial neural networks and Levenberg-Marquardt algorithm

    , Article European Journal of Medicinal Chemistry ; Volume 43, Issue 3 , 2008 , Pages 548-556 ; 02235234 (ISSN) Jalali Heravi, M ; Asadollahi Baboli, M ; Shahbazikhah, P ; Sharif University of Technology
    A linear and non-linear quantitative structure-activity relationship (QSAR) study is presented for modeling and predicting heparanase inhibitors' activity. A data set that consisted of 92 derivatives of 2,3-dihydro-1,3-dioxo-1H-isoindole-5-carboxylic acid, furanyl-1,3-thiazol-2-yl and benzoxazol-5-yl acetic acids is used in this study. Among a large number of descriptors, four parameters classified as physico-chemical, topological and electronic indices are chosen using stepwise multiple regression technique. The artificial neural networks (ANNs) model shows superiority over the multiple linear regressions (MLR) by accounting 87.9% of the variances of antiviral potency of the heparanase... 

    QSAR modelling of integrin antagonists using enhanced bayesian regularised genetic neural networks

    , Article SAR and QSAR in Environmental Research ; Volume 22, Issue 3-4 , May , 2011 , Pages 293-314 ; 1062936X (ISSN) Jalali Heravi, M ; Mani Varnosfaderani, A ; Sharif University of Technology
    Bayesian regularised genetic neural network (BRGNN) has been used for modelling the inhibition activity of 141 biphenylalanine derivatives as integrin antagonists. Three local pattern search (PS) methods, simulated annealing and threshold acceptance were combined with BRGNN in the form of a hybrid genetic algorithm (HGA). The results obtained revealed that PS is a suitable method for improving the ability of BRGNN to break out from the local minima. The proposed HGA technique is able to retrieve important variables from complex systems and nonlinear search spaces for optimisation. Two models with 8-3-1 artificial neural network (ANN) architectures were developed for describingα 4β 7 and α 4β... 

    Spectrophotometric determination of sulfide based on peroxidase inhibition by detection of purpurogallin formation

    , Article Ecotoxicology and Environmental Safety ; Volume 91 , 2013 , Pages 117-121 ; 01476513 (ISSN) Ghadiri, M ; Kariminia, H. R ; Roosta Azad, R ; Sharif University of Technology
    This paper presents a new method for spectrophotometirc detection of sulfide applying fungal peroxidase immobilized on sodium alginate. The sensing scheme was based on decrease of the absorbance of the orange compound, purpurogallin produced from pyrogallol and H2O2 as substrates, due to the inhibition of peroxidase by sulfide. Absorbance of purpurogallin was detected at 420nm by using a spectrophotometer. The proposed method could successfully detect the sulfide in the concentration range of 0.6-7.0μM with a detection limit of 0.4μM. The kinetic parameters of Michaelis-Menten with and without sulfide were also calculated. Possible inhibition mechanism of peroxidase by sulfide was deduced... 

    Effects of short term and long term Extremely Low Frequency Magnetic Field on depressive disorder in mice: Involvement of nitric oxide pathway

    , Article Life Sciences ; Volume 146 , 2016 , Pages 52-57 ; 00243205 (ISSN) Madjid Ansari, A ; Farzam Pour, S ; Sadr, A ; Shekarchi, B ; Majid Zadeh, A. K ; Sharif University of Technology
    Elsevier Inc 
    Aims Previous reports on the possible effects of Extremely Low Frequency Magnetic Fields (ELF MF) on mood have been paradoxical in different settings while no study has yet been conducted on animal behavior. In addition, it was shown that ELF MF exposure makes an increase in brain nitric oxide level. Therefore, in the current study, we aimed to assess the possible effect(s) of ELF MF exposure on mice Forced Swimming Test (FST) and evaluate the probable role of the increased level of nitric oxide in the observed behavior. Main methods Male adult mice NMRI were recruited to investigate the short term and long term ELF MF exposure (0.5 mT and 50 Hz, single 2 h and 2 weeks 2 h a day). Locomotor...