Preparation and characterization of novel derivatives of chitosan and trimethyl chitosan conjugated with dipeptides and vitamin B12 as candidates for oral delivery of insulin

Chitosan and its derivatives are widely used in drug delivery systems due to their bio-degradebility, bio-compatibility and absorption enhancing properties. Many peptide and protein derived therapeutics cannot be administered through oral rout because of the proteolytic condition of gastro-intestinal tract and their low bio-availability. Insulin is a peptide drug which is widely used in diabetics as repeated daily injection. Due to the fact that there are receptors for didpeptides and vitamine B12 in small intestine, in this research work novel derivatives of chitosan and trimethyl chitosan conjugated with glycyl-glycine, alanyl-alaninie and vitamine B12 were synthesized and characterized. The structure of conjugates as well as substitution of different functional groups was confirmed by different instrumental analytical methods such as Fourier transform infrared, magnetic resonance, and X-ray diffraction spectroscopy. Nano-particles of aforementioned loaded with insulin were prepared and their size, surface electrical charge and morphology characterized and their release profile were studied. The results are promising and reveal that these new chitosan and trimethyl chitosan derivatives are potential vehicles for protein and peptide drug molecules.     

Removal of methylene blue from aqueous solution by electrophoretically deposited titania‐halloysite nanotubes coatings

Two‐component suspensions of titania and halloysite nanotubes (HNTs) were prepared in ethanol with 0.5 g/L (optimum concentration) of polyethyleneimine (PEI) and different wt% of HNTs. Kinetics of Electrophoretic deposition (EPD) decreased with increasing the HNTs content in suspensions due to their less mobility compared with titania particles. HNTs reinforced the microstructure of coatings and reduced or completely prevented from cracking during drying and heat‐treatment steps. Removal of methylene blue (MB) via adsorption by HNTs coatings was faster than its photocatalytic degradation by titania coating. Dispersion of HNTs (up to ≈30 wt%) in the matrix of titania resulted in the synergistic catalytic effect in MB removal. The synergistic effect was because of the shorter traveling distance of MB molecules adsorbed on HNTs toward the photocatalytic active site of titania particles in composite coatings. However, the synergistic effect was destroyed with increasing the HNTs content in coating. Difference between the amount of MB removed by titania and composite coatings increased at longer times (≥60 minutes). Mass transfer of MB adsorbed on HNTs toward the photocatalytic active sites of adjacent titania particles can compensate the decline in the mass transfer from solution at longer times.     

Evaluation of antimicrobial and dyeing properties of walnut (Juglans regia L.) green husk extract for cosmetics

Walnut green husk is one of the main waste products from walnut and could be used as a source of natural dyeing compounds such as juglone. The present study was conducted to evaluate the effective use of walnut green husk extract as a natural hair dye. Dyeing properties, fastness and antimicrobial behaviours of dyed hair and also a skin irritation test for natural hair dye on rat skin were examined. When the extract was mixed with ascorbic acid as a developer, ferrous sulphate as a mordant, and Aloe vera extract used as a secondary mordant and also a cosmetic ingredient, the reaction resulted in a dark‐brown colour on hair samples. The dyed hair exhibited appropriate colour strength having excellent morphology for a hair surface coated with dye molecules. In addition, the dyed hair possessed good resistance to washing and daylight fastness, without any irritant properties as shown in a rat model, although high concentrations of iron‐based mordant may be problematic for long‐term usage. This paper also suggests the use of natural mordants such as lactic and oxalic acids to avoid any probable risks. Walnut green husk extract was an appropriate natural hair dyeing agent in practice and showed maximum antimicrobial activity compared with semi‐synthetic and commercial hair dyes. The results demonstrated that walnut green husk can be used as an economical, valuable, eco‐friendly and safe source of dyeing and antimicrobial agents for cosmetic products.     

Ethanol production by Mucor indicus and Rhizopus oryzae from rice straw by separate hydrolysis and fermentation

Rice straw was successfully converted to ethanol by separate enzymatic hydrolysis and fermentation by Mucor indicus, Rhizopus oryzae, and Saccharomyces cerevisiae. The hydrolysis temperature and pH of commercial cellulase and β-glucosidase enzymes were first investigated and their best performance obtained at 45 °C and pH 5.0. The pretreatment of the straw with dilute-acid hydrolysis resulted in 0.72 g g^?1 sugar yield during 48 h enzymatic hydrolysis, which was higher than steam-pretreated (0.60 g g^?1) and untreated straw (0.46 g g^?1). Furthermore, increasing the concentration of the dilute-acid pretreated straw from 20 to 50 and 100 g L^?1 resulted in 13% and 16% lower sugar yield, respectively. Anaerobic cultivation of the hydrolyzates with M. indicus resulted in 0.36–0.43 g g^?1 ethanol, 0.11–0.17 g g^?1 biomass, and 0.04–0.06 g g^?1 glycerol, which is comparable with the corresponding yields by S. cerevisiae (0.37–0.45 g g^?1 ethanol, 0.04–0.10 g g^?1 biomass and 0.05–0.07 glycerol). These two fungi produced no other major metabolite from the straw and completed the cultivation in less than 25 h. However, R. oryzae produced lactic acid as the major by-product with yield of 0.05–0.09 g g^?1. This fungus had ethanol, biomass and glycerol yields of 0.33–0.41, 0.06–0.12, and 0.03–0.04 g g^?1, respectively.     

N ‐acetylcysteine–PLGA nano‐conjugate: effects on cellular toxicity and uptake of gadopentate dimeglumine

Gadolinium as a contrast agent in MRI technique combined with DTPA causes contrast induced nephropathy (CIN) and nephrogenic systemic fibrosis (NSF) which can reduce by usage of antioxidants such as N‐acetyl cysteine by increasing the membrane''s permeability leads to lower cytotoxicity. In this study, N ‐acetyl cysteine‐PLGA Nano‐conjugate was synthesized according to stoichiometric rules of molar ratios andafter assessment by FTIR, NMR spectroscopy and Atomic Force Microscopy (AFM) imaging was combined with Magnevist® (gadopentetate dimeglumine) and its effects on the renal cells were evaluated. MTT [3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐Diphenyltetrazolium Bromide] and cellular uptake assays have indicated relatively significant toxicity of magnevist (P  < 0.05) on three cell lines including HEK293, MCF7 and L929 compared to other synthesized ligands that shown no toxicity. Moreover, systemic evaluation has shown no notable changes of blood urea nitrogen (BUN) and creatinine in kidney of mice. In consequence, antioxidant effect was increased as well as the renal toxicity of the contrast agent reduced at the cell level. As a result, PLGA‐NAC nano‐conjugate can be a promising choice for decreasing the magnevist toxicity for treatment and prevention of CIN and will be able to open a new horizon to research on reduction of toxicity of contrast agents by using nanoparticles.Inspec keywords: blood, toxicology, nanofabrication, cellular biophysics, biomedical materials, nanoparticles, chromatography, cancer, biodegradable materials, biomedical MRI, kidney, pH, nanomedicine, patient treatment, diseases, atomic force microscopy, Fourier transform infrared spectraOther keywords: cellular toxicity, gadopentate dimeglumine, contrast agent, magnetic resonance imaging technique, diethylenetriamine pentaacetate, contrast‐induced nephropathy, nephrogenic systemic fibrosis, stoichiometric rules, molar ratios, dimethyl sulphoxide solution, chromatography techniques, nuclear magnetic resonance spectroscopy, atomic force microscopy imaging, Magnevist®, gadopentetate dimeglumine, renal cells, MTT cytotoxicity, human embryonic kidney‐293, L929 cell lines, in vitro conditions, cellular uptake assays, Magnevist uptake, antioxidant effect, renal toxicity, cell level, PLGA nanocarrier, acetylcysteine nanoconjugate, Magnevist toxicity, N‐acetylcysteine–PLGA nano‐conjugate, N‐acetyl cysteine‐poly‐lactic‐co‐glycolic acid nanoconjugate     

Evaluation of the moment-rotation curve of I beam-to-CFT column connection with endplate,using mechanical modeling

Through this study, a method is presented to estimate moment-rotation (M-) curve of I beam-to-the concrete filled tube (CFT) connections. This method is based on the components method in which components are analyzed and modeled as different mechanical models. These components are considered as springs with specific mechanical properties of stiffness, strength, and rigid bars. Their force-displacement relationship is assumed bi-linear and 3-linear. The connection behavior is assumed through assembling the stiffness of different components. In this study, connection of I beam-to-CFT column with bolted endplate connection under monotonic loading, which has been tested in the laboratory, is evaluated. It must be mentioned that those bolts which penetrated into the column depth have been used in order to create continuity between flanges of the column. The suggested method has been compared with the experimental test and the advanced finite element model in terms of stiffness, strength, and rotational capacity; moreover, its operation was satisfactory.     

H2-selective mixed matrix membranes modeling using ANFIS,PSO-ANFIS,GA-ANFIS

The novel contribution of the current study is to employ adaptive neuro-fuzzy inference system (ANFIS) for evaluation of H₂-selective mixed matrix membranes (MMMs) performance in various operational conditions. Initially, MMMs were prepared by incorporating zeolite 4A nanoparticles into polydimethylsiloxane (PDMS) and applied in gas permeation measurement. The gas permeability of CH₄, CO₂, C₃H₈ and H₂ was used for ANFIS modeling. In this manner, the H₂/gas selectivity as the output of the model was modeled to the variations of feed pressure, nanofiller contents and the kind of gas, which were defined as input (design) variables. The proposed method is based on the improvement of ANFIS with genetic algorithm (GA) and particle swarm optimization (PSO). The PSO and GA were applied to improve the ANFIS performance. To determine the efficiency of PSO-ANFIS, GA-ANFIS and ANFIS models, a statistical analysis was performed. The results revealed that the PSO-ANFIS model yields better prediction in comparison to two other methods so that root mean square error (RMSE) and coefficient of determination (R²) were obtained as 0.0135 and 0.9938, respectively. The RMSE and R² values for GA-ANFIS were 0.0320 and 0.9653, respectively, and for ANFIS model were 0.0256 and 0.9787, respectively.     

Energy production trend in Iran and its effect on sustainable development

The purpose of this study is to review the energy production trend from different energy resources in recent decades and its effect on sustainable energy production as one of the basic axis of sustainable development in Iran.Ninety nine percent of energy production in Iran comes from oil & gas and only 1% from renewable energy resources. Since Iran has very rich fossil energy resources, little attention has been paid to explore alternative ways of energy production. Majority of country's income is from oil & gas which put extra pressure on its natural resources. Continuing with the existing trend may lead to a path away from the goals of sustainable development, set for the country. Therefore, the sustainability study should be of interest to decision-makers.     

Modelling of multi-period multi-product production planning considering production routes

The multi-period multi-product (MPMP) production planning problems, generally, deal with matching production levels of individual products with fluctuated demands over planning horizon. The conventional MPMP optimisation models suffer from insufficient utilisation of available capacity of machines. This fallacy is due to inappropriate formulation of machine capacity and material handling constraints. In this study, a novel mathematical model is proposed to simultaneously optimise production quantities and provide information about managerial decisions such as subcontracting, carrying inventory/backordering, and also hiring/layoff personnel. The problem is then formulated as a mixed integer linear programming (MILP) model by applying appropriate linearisation of non-linear components. The objective is to minimise production costs comprising of production, storage, shortage, subcontracting costs and costs associated with hiring/dismissing labourers. Superiority of the proposed model over existing ones, has been initially evaluated by solving the case presented by Byrne and Bakir [Byrne, M.D. and Bakir, M.A., 1999. Production planning using a hybrid simulation-analytical approach. International Journal of Production Economics, 59 (1), 305–311], and then evaluated by comparing the results obtained from solving both the proposed and the conventional MPMP production planning models using a 100-randomly-generated-test-problem.     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.