Eight-hydroxyguanosine (8-OHdG) is considered as one of the principle forms of oxygen radicals that stimulated the oxidative stress and has been extensively utilized as a biomarker for oncogenesis. The primary goal of the present study was to investigate the alteration in the levels of 8-OHdG, antioxidant profile and proinflammatory cytokines levels in patients with lung carcinoma. Blood samples were collected from 40 cases with lung cancer (stage III) admitted before the treatment, for health examination at the Nanakaly Hospital in Erbil city and 45 healthy samples of controls with ages ranging between 38-69 years for both groups. Circulating concentration of 8-OHdG, tumor necrosis factor and interleukin-6 were evaluated by ELISA. Circulating levels of superoxide dismutase (SOD), peroxidase (POX) and ascorbic acid (vitamin C) levels were also analyzed by using ELISA. The current work proposes that (8-OHdG) can be used as a functional biological marker, considering oxidative stress among the patients with lung carcinoma. The obtained data also indicated a correlation between serum cytokine concentrations and the rate of survival in lung carcinoma patients.
Back ground: Type 2 Diabetes mellitus (T2D) is a common complication of all liver diseases. However clinical and experimental data suggest a direct role of HCV in the perturbation of glucose metabolism. The aim of this study is to investigate the role of HCV infection as a risk factor to develop type 2 diabetes mellitus, and to study the immunopathogenicity of HCV in diabetes mellitus patients, through the assessment of IFN-γ, TNF- α and IL-10 serum levels.
Objectives: Is to investigate the role of HCV infection as a risk factor to develop type 2 diabetes mellitus, and to study the immunopathogenecity of HCV in diabetes mellitus patients, through the assessment of IFN-γ, TNF- α and IL-10 serum levels.
Recycling process presents a sustainable pavement by using the old materials that could be milled, mixed with virgin materials and recycling agents to produce recycled mixtures. The objective of this study is to evaluate the impact of water on recycled asphalt concrete mixtures, and the effect of the inclusion of old materials into recycled mixtures on the resistance of water damage. A total of 54 Marshall Specimens and 54 compressive strength specimens of (virgin, recycled, and aged asphalt concrete mixtures) had been prepared, and subjected to Tensile Strength Ratio test, and Index of Retained Strength test. Four types of recycling agents (used oil, oil + crumb rubber, soft grade asphalt cement, and asphalt cement + Su
... Show MoreThis study is conducted to evaluate the therapeutic and antioxidant effect of lemon juice on some hematological and biochemical parameters. Thirty female mice used in this study were exposed to oxidative stress through giving them hydrogen peroxide in drinking water for 30 days. Animals randomly distributed over 3 groups, each group contained 10 animals and treated as follows: T1 control group (drinking distilled water only), T2 (0.75% hydrogen peroxide in drinking water) and T3 (0.75% hydrogen peroxide in drinking water with daily drenching with 1 mL lemon juice). At the end of the experiment, blood samples were collected from animals for evaluating the following hematological and biochemical parameters: Haemoglobin concentration (Hb),
... Show MoreAcute lymphoblastic leukemia (ALL) is one of the commonest hematological malignancies affecting children and adults. Recent evidence suggests an involvement of Epstein-Barr virus (EBV) in ALL pathogenicity. Epigenetic aberration, especially altered DNA methylation marks, is a key event of cancer development. The present study aims to investigate how the ALL epimethylome reacts to viral infection through the assessment of the total 5-methylcytosine (5mC) levels in ALL patients, according to EBV infection. The 5mC global DNA methylation levels in 50 diagnosed ALL patients (age mean 26.23 yrs; age range 10-60 yrs) and 25 age-matched healthy controls were assessed using MethylFlash™ Methylated DNA Quantification Kit. Acute pri
... Show MoreLung cancer, similar to other cancer types, results from genetic changes. However, it is considered as more threatening due to the spread of the smoking habit, a major risk factor of the disease. Scientists have been collecting and analyzing the biological data for a long time, in attempts to find methods to predict cancer before it occurs. Analysis of these data requires the use of artificial intelligence algorithms and neural network approaches. In this paper, one of the deep neural networks was used, that is the enhancer Deep Belief Network (DBN), which is constructed from two Restricted Boltzmann Machines (RBM). The visible nodes for the first RBM are 13 nodes and 8 nodes in each hidden layer for the two RBMs. The enhancer DBN was tr
... Show MoreIn fish, a complex set of mechanisms deal with environmental stresses including hypoxia. In order to probe the hypothesis that hypoxia-induced stress could be manifested in varieties of pathways, a model species, mirror carp (Cyprinus carpio), were chronically exposed to hypoxic condition (dissolved oxygen level: 1.80±0.6mg/l) for 21 days and subsequently allowed to recover under normoxic condition (dissolved oxygen level: 8.2±0.5mg/l) for 7 days. At the end of these exposure periods, an integrated approach was applied to evaluate several endpoints at different levels of biological organisation. These included determination of (i) oxidative damage to DNA in erythrocytes (using modified comet assay), (ii) lipid peroxidation in liver sample
... Show MoreBackground: The diagnosis of interstitial lung disease (ILD) is frequently delayed, because clinical clues are neglected and respiratory symptoms are ascribed to more common pulmonary diagnosis such as asthma and chronic obstructive pulmonary disease in the primary care setting.
Objective: To evaluate the diagnostic yield of open lung biopsy in patients with suspected ILD in relation to clinical and radiological features.
Patients and methods: Thirty-five patients were admitted with suspected interstitial lung disease (ILD), and scheduled for open lung biopsy (OLB) in Ghazi AL-Hariri hospital for surgical specialty, were included in this study. Data collected from the patient's files (who were subjected to open lung biopsies which
Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreBackground: Chronic hyperglycemia causes diabetic nephropathy(DN), which is a typical microvascular complication of type 2 diabetes mellitus. The pathogenesis of DN is not fully understanding. The inflammation may possess a significant role in the progression of DN in diabetic patients. Method: The study accomplished at teaching laboratories of medical city, Baghdad, Iraq. It was included 50uncontrolled diabetic type 2 patients with nephropathy, age range (40-78) years and 42 controlled diabetics type 2 without nephropathy, age range (35 - 52) years as a control group. The participants divided in to two groups according to HbA1c measurement which is described as follows: < 7.5% of HbA1c describes controlled diabetes, and > 9% of HbA1c
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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