Hossein Attar

Research Field

Nonylphenol

10.1016/j.scp.2023.101308

Cite

Citations (2)

Artificial Neural Networks Modeling of Release of Olanzapine From Glycerol Monooleate Matrices

Letters in Drug Design & Discovery (2013)

Gita Bagheri Ebrahim Vasheghani‐Farahani Mehdi Ardjmand Hossein Attar Farid Abedin Dorkoosh

The important aim of this research was to develop an appropriate model to predict relationships between three casual factors on the responses based on an artificial neural network (ANN). As model formulation, 28 types of gels were prepared. The weight ratio of GMO/water (w/w) and PEG 300/GMO (w/w), percentage of Olanzapine (OZ) were selected as input data. Entrapment efficacy, maximum percentage of release, particle size and viscosity were estimated as gel characterization. A set of gel characterization and input data were employed as tutorial data for ANN methodology by using neural network toolbox in Matlab. Different topologies have been performed in order to determine the single network with good performance and accuracy. Four training algorithms (Levenberg–Marquardt, Bayesian- Regularization, BFGS Quasi-Newton, and Gradient Descent) were applied to train ANNs containing different numbers of hidden layers with various nods. The ability to predict the responses of all the algorithms were in the order of: BR > LM >BFGS> GD. Keywords: Artificial neural network, Multilayer perceptron, Training algorithms, Olanzapine, Glycerol monooleate.

Broyden–Fletcher–Goldfarb–Shanno algorithm

Perceptron

Multilayer perceptron

10.2174/1570180811666131227193958

Cite

Citations (2)

INCREASING THE YIELD OF ERYTHROMYCIN FERMENTATION USING IRON-OXIDE NANOPARTICLES

Ghazal Labbeiki Hossein Attar Amir Heydari Nasab Seyed Mahdi Rezayat Alimorad Rashidi

Source

Cite

Citations (0)

Heat-treated Saccharomyces cerevisiae for antimony speciation and antimony(III) preconcentration in water samples

Analytica Chimica Acta (2008)

Sébastien Marcellino Hossein Attar Didier Lièvremont Marie‐Claire Lett F Barbier

10.1016/j.aca.2008.09.031

Cite

Citations (30)

Patulin removal from synbiotic apple juice using Lactobacillus plantarum ATCC 8014

Journal of Applied Microbiology (2018)

Alaleh Zoghi Kianoush Khosravi‐Darani Sara Sohrabvandi Hossein Attar

The aim of this study was to evaluate the elimination of patulin (PAT) by Lactobacillus plantarum ATCC 8014 from artificially contaminated apple juice and its dependence on prebiotic, citric acid and ascorbic acid content.A central composite design was used for studying each of the three factors at five levels to find the optimum concentrations. The results showed that inserting 2·3% (w/v) fructooligosaccharide, 213 mg l-1 ascorbic acid and 1·4 g l-1 citric acid to apple juice with inoculating 3·6 × 1011 CFU per ml, L. plantarum improved the efficiency of PAT removal to 95·91% during 6 weeks cold storage. SDS-PAGE of cell surface proteins of probiotics revealed that surface layer proteins have an important role in PAT removal from apple juice. No significant difference was observed in the flavour and colour of the optimized synbiotic apple juice and in the control sample until 3 weeks of cold storage.Lactobacillus plantarum ATCC 8014 is capable of PAT removal from artificially contaminated synbiotic apple juice.Synbiotic apple juice artificially contaminated with PAT will be safe for consumers after the first day of probiotic inoculation; and surface layer proteins of probiotic cells are responsible for PAT removal.

Patulin

10.1111/jam.14172

Cite

Citations (43)

Microencapsulation of Saccharomyces cerevisiae using a Novel Sol-Gel Method and Investigate on its Bioactivity

Asian Journal of Biotechnology (2010)

Amir Mellati Hossein Attar Meysam Farahani

10.3923/ajbkr.2010.127.132

Cite

Citations (7)

DETERMINATION OF AZITHROMYCIN CRYSTALS MORPHOLOGY WILL BE DONE IN SUBSEQUENT CHANGING CONDITIONS AND THE TYPE OF CRYSTALLIZATION PROCESS CHANGE

Davood Razzaghi Hossein Attar Atefeh Molaei S A Shobayryan