This study was aimed to produce AuNPs biologically using Klebsiella pneumoniae and study their synergistic effect with some antibiotics.Technologies of nanoparticles are quick and are employed in many applications in biomedicine. The potential of metallic nanoparticle as an anti-microbial agent is greatly investigated which considered as an alternative method to reduce the challenges of multi-drug resistance microbes. The present study discusses the novel approach to synthesize nanoparticles involving eco-friendly synthesis of gold nanoparticles using Klebsiella pneumoniae and study their effect as antimicrobial spectrum .Also study synergism effect of gold nanoparticles with antibiotic against Acinetobacter baumannii. These approaches are used to enhance antimicrobial efficacy of nanoparticles by modification of surfaces and to investigate activity of antibiotic delivery.
Aim This study is an overview of NPEV investigated during AFP surveillance programs for the period 2010–2017 in Iraq. Methods Stool samples from 4296 AFP cases and 2933 healthy contacts among children less than 15 years of age were processed for virus isolation as a part of AFP surveillance for the Global Polio Eradication Program in Iraq at National Polio Laboratory. NPEV detection was performed by virus isolation on cell culture according to WHO recommendations. Results The NPEV isolation rate was 14% of total AFP cases and 14.5% of healthy contacts. The infection rate was higher in males than females with a male/female ratio of 1.5: 1. The highest NPEV infection rate was observed among the children aged 1-2 years and decrease significa
... Show MoreThe support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample
... Show MoreThe alterations in glyoxylate reductase and hydroxy-pyruvate reductase concentrations in the sera and the genetic alterations associated with calcium oxalate kidney stones in Iraqi patients were not studied previously so this study aimed to focus on these points. This study included 80 subjects; they were 50 patients with calcium oxalate stones compared to 30 apparently healthy controls. Biochemical investigations for kidney functions (creatinine, urea, and uric acid), were performed on the sera of both groups. Also, complete blood count, random blood sugar, and blood group tests. Furthermore, urine had been collected for General Urine Examination to visualize oxalate crystals in the urine of the patient. Also, the GRHPR
... Show MoreHepatitis B virus (HBV) infection is a serious disease of the liver and signifies a major worldwide health concern. HBV Genotyping is vital for further epidemiological study, predicting the disease outcome and response to treatment. The current study aimed to determine hepatitis B virus genotypes in patients with chronic hepatitis B, and to validate possible associations with the baseline characteristics of the disease. A total of 90 patients with chronic hepatitis B infection were enrolled in this study. Liver function tests, hepatitis B virus markers and DNA viral load were done using routine standardized procedures. HBV genotyping was performed using real time PCR. Genotype D was the most predominant in 64 (71.1%) of samples, while
... Show MoreWorldwide, hundreds of millions of people have been infected with COVID-19 since December 2019; however, about 20% or less developed severe symptoms. The main aim of the current study was to assess the relationship between the severity of Covid-19 and different clinical and laboratory parameters. A total number of 466 Arabs have willingly joined this prospective cohort. Out of the total number, 297 subjects (63.7%) had negative COVID-19 tests, and thus, they were recruited as controls, while 169 subjects (36.3%) who tested positive for COVID-19 were enrolled as cases. Out of the total number of COVID-19 patients, 127 (75.15%) presented with mild symptoms, and 42 (24.85%) had severe symptoms. The age range for the partic
... Show MoreThe high temperature superconductor’s compounds are one of the hot spot field of science, due to their applications in industries. Hg0.8Sb0.2Ba2Ca2Cu3O8+δ and Hg0.8Sb0.2Ba2Ca1Cu2O6+δ, were manufactured using a doable-step of solid state reaction method. The samples were sintered at 800 ° C. The transition temperatures Tc are found from electrically resistively by using four probe techniques. The resistivity become zero when the transition temperature Tc(offset) have 131 and 119 K, and the onset temperature Tc(onset) have 139 K for Hg0.8Sb0.2Ba2Ca2Cu3O8+δ and 132 K for Hg0.8Sb0.2Ba2Ca1Cu2O6+δ. Analysis of X-ray diffraction showed a tetragonal structure with lattice parameters changes for all samples.
Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
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