Background: Accurate detection of thyroid autoantibodies by enzyme linked immunosorbant assay technique namely thyroglobulin antibody, thyroid peroxides antibody is crucial in the differentiation of autoimmune thyroid disorders from other form of thyroid diseases.
Objective: Evaluation of the detection of thyroglobulin antibody and thyroid peroxides antibody in different thyroid diseases using enzyme linked immunosorbant assay technique.
Methods: - Seventy-five patients admitted to Surgical Units of Baghdad Medical City Hospital for the period between "October 2010 to June 2011" they were waiting to do thyroidectomy. They were chosen nonselectively for serological evaluation of above autoantibodies , and correlation of the results

Titanium-dioxide (TiO₂) nanoparticles suspended in water, and ethanol based fluids have been prepared using one step method and characterized by scanning electron microscopy (SEM), and UV–visible spectrophotometer. The TiO₂ nanoparticles were added to base fluids with different volume concentrations from 0.1% to1.5% by dispersing the synthesized nanoparticles in deionized water and ethanol solutions. The effective thermal conductivity, viscosity and pH of prepared nanofluids at different temperatures from 15 to 30 ^oC were carried out and investigated. It was observed that the thermal conductivity, pH, and viscosity of nanofluids increases with the increase in TiO₂ nanoparticle volume fraction

Liquid electrodes of domperidone maleate (DOMP) imprinted polymer were synthesis based on precipitation polymerization mechanism. The molecularly imprinted (MIP) and non-imprinted (NIP) polymers were synthesized using DOMP as a template. By methyl methacrylate (MMA) as monomer, N,Nmethylenebisacrylamide (NMAA) and ethylene glycol dimethacrylate (EGDMA) as cross-linkers and benzoyl peroxide (BP) as an initiator. The molecularly imprinted membranes were synthesis using acetophenone (APH), di-butyl sabacate (DBS), Di octylphthalate (DOPH) and triolyl phosphate (TP)as plasticizers in PVC matrix. The slopes and limit of detection of l

     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

In this study, an improved process was proposed for the synthesis of structure-controlled Cu2O nanoparticles, using a simplified wet chemical method at room temperature. A chemical solution route was established to synthesize Cu2O crystals with various sizes and morphologies. The structure, morphology, and optical properties of Cu2O nanoparticles were analyzed by X-ray diffraction, SEM (scanning electron microscope), and UV-Vis spectroscopy. By adjusting the aqueous mixture solutions of NaOH and NH2OH•HCl, the synthesis of Cu2O crystals with different morphology and size could be realized. Strangely, it was found that the change in the ratio of de-ionized water and NaOH aqueous solution led to the synthesis of Cu2O crystals of differen

Laser is a powerful device that has a wide range of applications in fields ranging from materials science and manufacturing to medicine and fibre optic communications. One remarkable

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when