Methicillin resistant Staphylococcus aureus (MRSA) is one of the principal nosocomial causative agents. This bacterium has the capability to resist wide range of antibiotics and it is responsible for many diseases like skin, nose and wounds infection. In this study, randomly amplified polymorphic DNA (RAPD)-PCR was applied with ten random primers to examine the molecular diversity among methicillin resistant Staphylococcus aureus (MRSA) isolates in the hospitals and to investigate the genetic distance between them. 90 Isolates were collected from clinical specimens from Iraqi hospitals for a total of 90 isolates. Only 10 strains (11.11%) were found to be MRSA. From these 10 primers, only 9 gave clear amplification products. 91 fragment lines were generated from these primers across all isolates with an average of 10 fragment lines per primer. Of these, 90 (99%) were polymorphic. The size of the amplified bands ranged between 145-2109 bp. The polymorphism percentage for all primers was 100% except OP-X17 primer which gave 86% polymorphism. The genetic distances revealed from Jaccard similarity index was calculated for the 90 RAPD polymorphic fragment lines. The highest genetic distance value 0.959 was between isolate number (1) and (5) and between isolate number (3) and (10), while the lowest genetic distance value 0.218 was between isolate number (6) and (7). This study shows that RAPD-PCR technique assayed with nine primers can be successfully applied to reveal the genetic distances among methicillin resistant Staphylococcus aureus (MRSA) isolates from different hospitals.
Arsenic is a prevalent and pervasive environmental contaminant with varied amounts in drinking water. Arsenic exposure causes cancer, cardiovascular, liver, nerve, and ophthalmic diseases. The current study aimed to find the best conditions for eliminating arsenic from simulated wastewater and their effect on biomarkers of hepatic in mice. Adsorption tests including pH, contact duration, Al-kheriat dosage, and arsenic concentrations were evaluated. Seventy-two healthy albino mice (male) were accidentally allocated into nine groups (n = 8), the first group was considered as healthy control, the second group (AL-Kheriat), and other groups received AL-Kheriat and arsenic 25, 50, 75, 100, 125, 150 and 175 mg/kg, respectively. Next 10 days, the
... Show MoreCarboxymethyl cellulose (CMC) is one of the important cellulose derivatives, and it can be developed as a host polymer for solid polymer electrolyte (SPE) membrane. This study aimed to synthesis of CMC from coconut fiber cellulose and it was applied to prepare the SPE membranes. Cellulose isolation was conducted through the delignification and bleaching process, while the CMC synthesis was conducted through alkalization and carboxymethylation treatments. SPE membranes were prepared by blending CMC with carboxymethyl chitosan (CMCh) (80/20) and mixed with various weight percentages of LiOAc at room temperature. SPE membranes characterizations were conducted using FTIR, EIS, XRD, SEM, and tensile testi
Many production companies suffers from big losses because of high production cost and low profits for several reasons, including raw materials high prices and no taxes impose on imported goods also consumer protection law deactivation and national product and customs law, so most of consumers buy imported goods because it is characterized by modern specifications and low prices.
The production company also suffers from uncertainty in the cost, volume of production, sales, and availability of raw materials and workers number because they vary according to the seasons of the year.
I had adopted in this research fuzzy linear program model with fuzzy figures
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This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro
... Show MoreExcessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M
... Show MoreBackground: Hypothyroidism is the most prevalent thyroid disorders worldwide. Hypothyroidism manifestations are wide spectrum, affecting various systems in human body including the nervous system. Hypothyroidism can cause neuropsychiatric symptoms such as anxiety, depression and diminishing in attention, memory and executive function. Aim: to investigate the level of anxiety and depression in patients with hypothyroidism receiving levothyroxine treatment. Method: a cross-sectional study was conducted at Baghdad Center for Nuclear Medicine and Radiation Therapy from March to June 2022. The study population included patients of both genders, aged 18-65 years, diagnosed with hypothyroidism, were receiving levothyroxine treatment and
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