Objectives: To study the spectrum and classification of ATP7B variants in Iraqi children with Wilson disease by direct gene sequencing with clinical correlation. Methods: Fifty-five unrelated children with a clinical diagnosis of Wilson disease (WD) were recruited. Deoxyribonucleic acid was extracted from peripheral blood samples, and variants in the ATP7B gene were identified using next-generation sequencing. Results: Seventy-six deleterious variants were detected in 97 out of 110 alleles of the ATP7B gene. Thirty (54.5%) patients had 2 disease-causing variants (15 homozygous and 15 compound heterozygous). Twelve (21.8%) patients had one disease-causing variant and one variant of uncertain significance (VUS) with potential pathogenicity. Thirteen (23.6%) patients were carriers of a single disease-causing variant. The most frequent variants, c.3305T>C and c.956delC, were detected in 4 alleles each, followed by c.3741-3742dupCA and c.3694A>C, which were detected in 3 alleles each. Among the 76 variants, 42 were missense, 13 were stop-gain, 9 were frameshift, 1 was an in-frame deletion, and 11 were intronic variants. Notably, the globally common variant H1069Q was not detected in this study. Conclusion: The mutational spectrum of ATP7B in the Iraqi population is diverse, despite the high rates of consanguinity. It differs from that of neighboring countries. We provided evidence for ten VUS to be reclassified as deleterious, raising questions about the diagnostic criteria for patients with higher Leipzig scores and a single deleterious variant.
Rheumatoid arthritis is a chronic systemic inflammatory disease. Inflammation leads to joint damage and increases the risk of cardiovascular diseases. Neutrophil lymphocyte ratio (NLR) is a measure of inflammation in many diseases. Therefore, we aimed to evaluate the usefulness of NLR to detect inflammation in RA, and its correlation to RA disease activity indices and some hematological parameters. A cross-sectional study involving 24 patients with active rheumatoid arthritis (RA) who are using MTX participated in this study. All patients were clinically evaluated using disease activity score of 28 joints (DAS28) and simplified disease activity index (SDAI), whereas functional disability was assessed by health assessment questionnaire di
... Show MoreBackground :Atherosclerosis is the most
frequent underlying cause of ischemic heart
disease and a major cause of death all over the
world. This study was carried out to analyze and
compare the angiographic findings in patients
with diabetes mellitus versus non diabetics with
coronary heart disease , and to correlate these
findings with some risk factors for coronary
heart disease.
Methods: A total of 100 patients were studied,
50 with diabetes mellitus, and 50 non diabetics.
This study was carried out at Al-Sadr teaching
hospital in Basrah, Southern Iraq during the
period April 2009- September 2009. All patients
were known to have coronary heart disease. Risk
factors for coronary heart disease
Image 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
... Show MoreBackground: Acute myeloid leukemia (AML) is an adult leukemia characterized by rapid proliferation of undifferentiated myeloid precursors, leading to bone marrow (BM) failure and impaired erythropoiesis. The p53 tumor suppressor protein regulates cell division and inhibits tumor development by preventing cell proliferation of altered or damaged DNA. It orchestrates various cellular reactions, including cell cycle arrest, DNA repair, and antioxidant properties. Objectives: To investigate the relationship of P53 serum level with hematological findings, remission, and survival status in de novo AML patients. Methods: This is a cross-sectional study that enrolled 63 newly diagnosed de novo AML patients, and 15 sex- and age-matched healt
... Show More