University of Tabriz

About: University of Tabriz is a education organization based out in Tabriz, Iran. It is known for research contribution in the topics: Population & Nanocomposite. The organization has 12141 authors who have published 20976 publications receiving 313982 citations.

Antibacterial properties of LDPE nanocomposite films in packaging of UF cheese

Abstract: The purpose of this study was to investigate antibacterial potential of low-density polyethylene (LDPE) packaging films incorporating silver (Ag), copper oxide (CuO) and zinc oxide (ZnO) nanoparticles in measuring of coliform amounts of ultra-filtrated (UF) cheese. The initial LDPE/nanoparticle composites were produced by melting extrusion followed by extruding the obtained composites through a die to achieve a film thickness of 45 ± 5 μm. The number of surviving coliform bacteria was decreased by 4.21 log cfu/g after 4 weeks of storage at 4 ± 0.5 °C, whilst pure LDPE films showed a reduction of only 1.04 log cfu/g. A composition of 0% Ag, 1% CuO, 0% ZnO gave an optimum point in combined design using Design Expert analysis. A suitable microbial model was suggested for retarding coliform bacteria growth in UF cheese. The difference between the optimum point of nanocomposite film and its repeat was not significant (p

Assessment of different methods for estimation of missing data in precipitation studies

Abstract: The outcome of data analysis depends on the quality and completeness of data. This paper considers various techniques for filling in missing precipitation data. To assess suitability of the different methods for filling in missing data, monthly precipitation data collected at six different stations was considered. The complete sets (with no missing values) are used to predict monthly precipitation. The arithmetic averaging method, the multiple linear regression method, and the non-linear iterative partial least squares algorithm perform best. The multiple regression method provided a successful estimation of the missing precipitation data, which is supported by the results published in the literature. The multiple imputation method produced the most accurate results for precipitation data from five dependent stations. The decision-tree algorithm is explicit, and therefore it is used when insights into the decision making are needed. Comprehensive error analysis is presented.

New Insights in to the Intrinsic and Acquired Drug Resistance Mechanisms in Mycobacteria.

Abstract: Infectious diseases caused by clinically important Mycobacteria continue to be an important public health problem worldwide primarily due to emergence of drug resistance crisis. In recent years, the control of tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (MTB), is hampered by the emergence of multidrug resistance (MDR), defined as resistance to at least isoniazid (INH) and rifampicin (RIF), two key drugs in the treatment of the disease. Despite the availability of curative anti-TB therapy, inappropriate and inadequate treatment has allowed MTB to acquire resistance to the most important anti-TB drugs. Likewise, for most mycobacteria other than MTB, the outcome of drug treatment is poor and is likely related to the high levels of antibiotic resistance. Thus, a better knowledge of the underlying mechanisms of drug resistance in mycobacteria could aid not only to select the best therapeutic options but also to develop novel drugs that can overwhelm the existing resistance mechanisms. In this article, we review the distinctive mechanisms of antibiotic resistance in mycobacteria.