Three hundred and sixty different samples were collected from different sources, including wound, burn, nasal, and oral swabs from several hospitals in Baghdad. A number of 150 (53%) Staphylococcus aureus samples were isolated and identified among a total of 283 samples. Then, the spread of the Toxic Shock Syndrome Toxin-1 gene (tsst-1) was investigated in β-lactamase resistant S. aureus. According to the source of samples, the distribution of S. aureus  isolates was found to be significantly higher (p < 0.01) in wound samples as compared to other sources. According to the age, a highly significant  distribution (p < 0.01) was recorded in the age group of 15-30 years,

Background: Type 1 diabetes mellitus is one of the most common chronic endocrine disorders of childhood, growth impairment is one of its long−term consequences

Objective: To study the anthropometric indices among children with type 1diabetes.
Results: A total of 253 children with type 1diabetes were studied, 51.8% were females, 47.9% developed the disease at 5-9 years of age, and 52.6% presented with classical signs and symptoms. Stunting /sever stunting was 15% with male predominance, higher among older age group (10-20 y), wasting/ sever wasting was 19.4% with male predominance, higher among older age group (10-20 y), over weight/ obese was 3.6% with females predominant an

      The study was conducted for the detection of Aflatoxin B1(AFB1) in the serum and urine of 42 early and middle childhood patients (26 male and  16 female ) with renal function disease, liver function disease, in additional to atrophy in the growth and other symptoms depending on the information within consent obtained from each patient, in addition to 8 children, apparently healthy, as  the control. The technique of HPLC was used for the detection of AFB1 from all samples. The results showed that out of 42 patient children, 19 (45.2%) gave positive detection of AFB1 in the serum among all age groups patients with a mean of 0.88 ng/ml and a range of (0.12-3.04) ng/ml. This was compared with the cont

Due to the increasing number of people with in Iraq, it has become necessary to treat seriously this problem, which was not considered significantly to the best of researcher knowledge. Thus, the current research aims to construct a scale to measure the physical down syndromes, which distinguish them from others. It consisted of (39) items. The researcher has presented some related literature that addressed the current problem

Background: Seasonal variation and gender preponderance have not been adequately studied in Guillain-Barre syndrome (GBS).
Objective: This study aims to evaluate the seasonal variation and sex preponderance in children with Guillian Barré Syndrome.
Patients and methods: A cross sectional study was carried out by reviewing wards’ registry of all cases with Guillian Barré Syndrome admitted to Children Welfare Teaching Hospital during a 10-year period (1999 - 2008). Age, sex, seasonal distribution, residence and outcome were analysed.
Results: Guillian Barré Syndrome was diagnosed in 217 (126 boys, 91 girls) patients and the annual hospital rate of admission was 22.9 /100000 children. There was increase annual incidence from 1

Background: Type 1 diabetes mellitus (T1DM) is a common disease in childhood. A linear relation between glycemic control (HbA1c < 7) and onset or progression of complication was detected. Only few individuals achieve glycemic control.
Objective: To estimate the glycemic control among diabetic children attending tertiary center.
Methods: All diabetic children registered in the diabetic consultancy clinic in Children Welfare Teaching hospital (298) were included in the study. Case records were reviewed and information on demography, weight and height, age at diagnosis and HbA1c was requested.
Results: Out of the total, 23.8% diabetic children had glycemic control. Glycemic control was decreasing with age (p=0.001), significantl

Back ground: Fibromyalgia syndrome (FMS) is a common chronic musculo-skeletal disorder resulting in chronic widespread pain impacting on quality life.
Objectives: To assess the relationship between FMS and knee osteoarthritis (KOA) and to evaluate the predictors of this relationship if present.
Patients and Methods: One hundred Iraqi KOA patients and 100 healthy controls were included in this cross-sectional study. Full history was taken and complete clinical examination was done for all patients. Baseline characteristics [age, sex, duration, body mass index (BMI), waist circumference, family history (Hx) of KOA, smoking history, and drug history.] were also documented. Laboratory analysis included complete blood count, erythrocyte

Background: Periodontitis is a long-standing infection that destroys the gums, periodontal ligaments, and the alveolar bone that supports the teeth. Inflammation of the gums and chronic periodontitis are both caused by the bacteria in the dental plaque and the herpes viruses, especially types 1 and 2 of the herpes simplex virus.

Objectives: To compare the ELISA and real-time PCR as ways to detect the herpes simplex virus in breast cancer pat

Background: Metabolic syndrome is a cluster of risk factors for atherosclerotic cardiovascular disease caused by abdominal obesity, such as hyperglycemia, hypertension, dyslipidemia, and insulin resistance.Adiponectin is a protein hormone that modulates a number of metabolic processes, including glucose regulation and fatty acidcatabolism. Adiponectin is exclusively secreted from adipose tissue into the bloodstream. Leptin, a hormone synthesized by fat tissue had been noted to regulate energy balance and metabolism.In this study investigated the relationships of adiponectin/leptin ratio with metabolic syndrome in apparently healthy Iraqi male adults.
Objective: This study was designed to investigate the r

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D