Multiple sclerosis (MS) is a chronic, inflammatory demyelinating disease of central nervous system with complex etiopathogenesis that impacts young adults (Lee et al., 2015), and MS impacts younger and middle aged character and leads to a range of disabilities that can alter their daily routines (Yara et al, 2010). Although, the exact cause of MS is still undetermined, the disease is mediated by adaptive immunity through the infiltration of T cells into the central nervous system (Bjelobaba et al, 2017). MS causes the Focal neurological symptomsand biochemical changes in the molecular level and the variation of neural cells such as loss or alteration of sensation, motor function, visible signs such as blurred vision or transient blindness, disturbance of conjugate eye movements, bladder and bowel dysfunction and cognitive impairment (Induruwa et al, 2012 and Jafarzadeh et al, 2014). Autoimmune diseases (ADs) are chronic conditions initiated by way of the loss of immunological tolerance to self-antigens (TodorovicDilas et al, 2011). It is a heterogeneous group of disorders in which more than one modification in the immune system can be specific to a particular tissue or organ or might also be systemic, non-specific, involving multiple tissues or organs (Ray et al, 2012). One possible cause behind this is a lack of understanding of pathogenic mechanisms driving progressive multiple sclerosis. Due to the indolent nature of symptom progression, current disease criteria used to signify the course of disease (Lublin et al, 2014) indicate diagnosis is generally retrospective and based totally on history of gradual worsening. Clearly, diagnosis is primary based on clinical judgment, as there is no fully reliable diagnostic test (Ontaneda et al, 2015). In latest years, the elements involved in the etiology of the disease have also included oxidative stress (OS), which is described as an imbalance between the generation of reactive oxygen species (ROS) and the mechanisms that are responsible for their elimination, andthe imbalance between OS agents and antioxidants leads to OS activating the inflammatory process (Phaniendra et al, 2015). In the absence of enough antioxidant defenses, ROS can reason oxidative damage to macromolecules resulting in oxidation of lipids, proteins and deoxyribonucleic acid (DNA) (Griffiths, 2002). Some reseach report that ROS play a main role in myelin phagocytosis (Ghabaee et al, 2010 and Tasset et al, 2012). The inflammatory response gives rise to the manufacturing of both ROS and Reactive Biochem. Cell. Arch. Vol. 19, No. 1, pp. 31-35, 2019 www.connectjournals.com/bca ISSN 0972-5075 Nitrogen Species RNS through monocyte interactions with brain endothelium; ROS manufacturing induces cytoskeletal rearrangements, loss of blood-brain blood BBB integrity, tight-junction alteration and the extravasation of leukocytes into the central nervous system (Van et al, 2011; Witherick et al, 2011). Aim of study The aim of this study focuses on determination 8-H2-dG, MDA and PON1 in multiple sclerosis disease and finds the relationship between newly marker 8-H-2-dG with MDA and PON1. MATERIALS AND METHODS Subjects This study was performed on 25 female patients with age (25-35) years who diagnosed by physicians as a multiple sclerosis in Misan governorate. The patients compared with 25 apparently healthful in the identic rangel of age. In this study sample was collected five mL of venous bloods, placed in to plain tubes until coagulation was performed. Serum was separated from blood cells by centrifugation 4000 r.p.m. Assay method Determination of serum of 8-H-2-dG This assay that can be used for quantification of 8- H-2-dG in urine, cell culture, plasma and other sample matrices. The ELISA utilize an 8-H-2-dG coated plate and HRP- conjugated antibody or detection which allows for any assay range of 0.94-60 ng/mL, with sensitivity of 0.59 ng/mL. Determination of MDA The concentration of MDA,which is the consequence of lipid peroxidation and a marker of oxidative stress, was measured using thiobarbiturc acid. Determination of PON1 The quantitive sandwich enzyme immunoassay (ELISA) technique was employed for determination of PON1.
The study was conducted at the fields of the Department of Horticulture and Landscape Gardening, College of Agriculture Engineering Sciences, University of Baghdad. During the spring 2017. All the recommended practices were followed during experimentation. The experimental material consisted four Genotype it is Batraa, Btera, Mosulle, and local selection. The experiment was applied in Randomized Complete Block Design (RCBD). The objectives of Study were to estimate the some genetic parameters and path coefficient for some traits Okra, The results of statistical analysis for these genotypes were highly significant differences for all traits except the traits number of leaves, the numbe
The present investigation focuses on the response of simply supported reinforced concrete rectangular-section beams with multiple openings of different sizes, numbers, and geometrical configurations. The advantages of the reinforcement concrete beams with multiple opening are mainly, practical benefit including decreasing the floor heights due to passage of the utilities through the beam rather than the passage beneath it, and constructional benefit that includes the reduction of the self-weight of structure resulting due to the reduction of the dead load that achieves economic design. To optimize beam self-weight with its ultimate resistance capacity, ten reinforced concrete beams having a length, width, and depth of 2700, 100, and
... Show MoreAspartate aminotransferase was purified from urine and serum of patients with type 2 diabetes in a 2 steps procedure involving dialysis bag and sephadex G-25 gel filtration (column chromatography). The enzyme was purified 346.23 fold with 1467% yield and 3.46 fold with 142.85% yield in urine and serum of patients with type 2 diabetes respectively. The purified enzyme showed single peak. The results of this study revealed that AST activity of type 2 diabetes urine and serum increased significantly (p<0.001) compared with control group.
Background: While two-thirds of breast cancers express hormone receptors for either estrogen (ER) and/or progesterone (PR) , genetically altered PI3K pathway was found in more than 70% of ER-positive breast cancers.An aberrant activity of cyclin-dependent kinase 1 (CDK1) in a wide variety of human cancers has selectively constituted an attractive pharmacological targets in MYC-dependent human breast cancer cells.
Aim of the study: Role of p110-beta as well as and CDK 1 in the pathogenesis of subset of breast cancers and contribution in their carcinogenesis.
Type of the study: is a retrospective study
Methods: This retr
... Show MoreA total of 33 Iraq male positive for Toxoplasmosis and Iraq male negative for Toxoplasmosis (controls) were studies to Evaluation of some biochemical and immunological parameters changes.The parameters included lipid profile such as (Cholesterol(C), Triglycerides(TG), High-Density Lipoprotein (HDL), Low-Density Lipoprotein (LDL) and very Low-Density Lipoprotein (VLDL) and complement component C3 and C4. The results revealed significant decrease in the total cholesterol, Triglycerides, LDL and non-significant in vLDL (129.96±1.63, 130.69± 2.80, 87.19±1.97, 29.24± 0.83 mg/dl respectively) and non-significant increase in HDL(24.22 ±0.62) mg/dl compared with control group(152.07± 1.63, 156.48± 6.55, 99.26 ±1.39, 31.49± 1.30 and 21.31±
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Detection of virulence gene agglutinin-like sequence (ALS) 1 by using molecular technology from clinical samples (