Gestational diabetes mellitus (GDM) is a complication of gestation that is characterized by impaired glucose tolerance with first recognition during gestation. It develops when ?- cell of pancreas fail to compensate the diminished insulin sensitivity during gestation. This study aims to investigate the relationship between mother adiponectin level and ?- cell dysfunction with development gestational diabetes mellitus (GDM) and other parameters in the last trimester of pregnancy. This study includes (80) subjects ( pregnant women) in the third trimester of pregnancy, (40) healthy pregnant individuals as control group aged between (17 - 42) years and (40) gestational diabetes mellitus patients with aged between (20 - 42) years. The f

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Background:The most common pattern of dyslipidemia in diabetic patients is increased triglyceride (TG) and decreased HDL cholesterol level, The concentration of LDL cholesterol in diabetic patients is usually not significantly different from non diabetic individuals, Diabetic patients may have elevated levels of non-HDL cholesterol [ LDL+VLDL]. However type 2 diabetic patients typically have apreponderance of smaller ,denser LDL particles which possibly increases atherogenicity even if the absolute concentration of LDL cholesterol is not significantly increased. The Third Adult Treatment Panel of the National Cholesterol Education Program (NCEP III) and the American Heart Association (AHA ) have designate diabetes as a coronary heart dis

Background: Diabetic neuropathy can affect any peripheral nerve, including sensory neurons, motor neurons, and the autonomic nervous system. Therefore, diabetic neuropathy has the potential to affect essentially any organ and can affect parts of the nervous system like the optic nerve, spinal cord, and brain. In addition, chronic hyperglycemia affects Schwann cells, and more severe patterns of diabetic neuropathy in humans involve demyelization. Schwann cell destruction might cause a number of changes in the axon. study aims to evaluate serum myelin protein level as a predicting marker in the diagnosis of diabetic neuropathy and to prevent early neuropathy complications of type 2 diabetes.

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The infection with H. Pylori stimulates a signaling cascade that causes the generation of Cytokines and provokes Oxidative stress that is involved in the chronic inflammatory response leads to Gastric cancers. Reactive oxygen species (ROS) produce 8-Hydroxydeoxyguanosine (8-OHdG), the persistent oxidative DNA damage product. The study objective was to assess if there was a link between inflammatory cytokine levels and the presence of Oxidative DNA damage in Gastric tumor patients. In addition, evaluation of the diagnostic and prognostic value of Oxidative DNA damage and inflammatory cytokine biomarkers for Stomach cancers is being conducted. The study was accomplished on medically diagnosed Stomach cancer patients before any form of trea

Introduction and Aim: Forkhead box P3 (FOXP3) and interleukin-10 (IL-10) are the key regulators controlling the activity of Treg cells, which are crucial for maintaining immune tolerance and reducing autoimmune reactions. The objective of this study was to investigate the potential utility of elevated levels of FOXP3 and IL-10 gene expression as a diagnostic indicator in patients with rheumatoid arthritis (RA).   Materials and Methods: The study used quantitative polymerase chain reaction (qPCR) to examine the expression levels of FOXP3 and IL-10 transcripts in whole blood samples from Iraqi patients with rheumatoid arthritis. A group of healthy control subjects were also included in the study.   Results: In blood samples taken fr

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Background: We aimed to investigate the accuracy of salivary matrix metalloproteinases (MMP)-8 and -9, and tissue inhibitor of metalloproteinase (TIMP)-1 in diagnosing periodontitis and in distinguishing periodontitis stages (S)1 to S3. Methods: This study was a case–control study that included patients with periodontitis S1 to S3 and subjects with healthy periodontia (controls). Saliva was collected, and then, clinical parameters were recorded, including plaque index, bleeding on probing, probing pocket depth, and clinical attachment level. Diagnosis was confirmed by assessing the alveolar bone level using radiography. Salivary biomarkers were assayed using an enzyme-linked immunosorbent assay. Results: A total of 45 patients (15