Abstract Background Hemoglobin A1c (HbA1c) is a widely used test for glycemic control. It is done for chronic kidney disease (CKD) patients. Renal disease is accompanied by thyroid abnormalities, which affect HbA1c, especially in those taking erythropoiesis-stimulating agents (ESAs). We aimed to find the effect of thyroid dysfunction on HbA1c in hemodialysis patients taking ESAs and those who do not. Materials and Method Fifty six patients were included in this study, which was done between September 2017 and June 2018, in Baghdad Teaching Hospital. Thyroid stimulating hormone, free T3, free T4 and HbA1c measurements were done. The patients were divided into 2 groups; those who took ESAs and those who did not, then they were subdivided into

Background: Hemoglobin A1c (HbA1c) is a widely used test for glycemic control. It is done for chronic kidney disease (CKD) patients. Renal disease is accompanied by thyroid abnormalities, which affect HbA1c, especially in those taking erythropoiesis-stimulating agents (ESAs). We aimed to find the effect of thyroid dysfunction on HbA1c in hemodialysis patients taking ESAs and those who do not. Materials and Method: Fifty six patients were included in this study, which was done between September 2017 and June 2018, in Baghdad Teaching Hospital. Thyroid stimulating hormone, free T3, free T4 and HbA1c measurements were done. The patients were divided into 2 groups; those who took ESAs and those who did not, then they were subdivided into those

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

Aqueous root extract has been used to examine the green production of silver nanoparticles (AgNPs) by reducing the Ag+ ions in a silver nitrate solution. UV-Vis spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced AgNPs. The AgNPs that were created had a maximum absorbance at 416 nm, were spherical in form, polydispersed in nature, and were 685 nm in size.The AgNPs demonstrated antibacterial efficacy against Escherichia coli and Staphylococcus. The dengue vector Aedes aegypti's second instar larvae were very susceptible to the AgNPs' powerful larvicidal action.

In this work, silver (Ag) self-metallization on a polyimide (PI) film was prepared through autocatalytic plating. PI films were prepared through the solution casting method, followed by etching with potassium hydroxide (KOH) solution, sensitization with tin chloride (SnCl₂), and the use of palladium chloride (PdCl₂) to activate the surface of PI. Energy-dispersive X-ray analysis (EDX) showed the highest peak in the (Ag) region and confirmed the presence of AgNPs. The diffraction peaks at 2θ = 38.2^°, 44.5^°, 64.6^°, and 78.2^° represented the 111, 200, 220, and 311 planes of Ag, respectively. The FT–IR an

Epoxy resins were modified by some thermosetting materials using unsaturated polyesters which were cured with styrene , MMA ,and MA . When unsaturated Polyester ( as thermosetting material ) was used , and cured with styrene showed better results than acrylic monomers . Thermal stability rised on modification of epoxy resins with unsaturated polyester . The new formulation had converted the epoxy resin from hard brittle material to hard and tough material .

Thermal analysis were studied using ( DSC ) and physicomechanical characteristics were measured .

Hemogloin (Hb) and serum ferritin levels are used to assess anemia in pregnancy. Some studies referred to the influence of maternal age, body mass index (BMI) and parity on Hb and serum ferritin levels. The study aimed to examine the possible association of maternal Hb and serum ferritin with maternal age, parity, and BMI in a sample of pregnant women in Baghdad.

 Ninety healthy pregnant women, grouped in three equal groups according to the pregnancy trimester, and thirty apparently healthy non-pregnant women from Baghdad were enrolled in this observational study.  Blood and serum samples were obtained for the estimation of Hb and serum ferritin levels.

The pooled data of participants showed a n