The aim of this study was investigating the correlation between elevation of Prolactin levels and the increase of the concentrations of total sialic acids. The study was performed on 149 women consisted of 93 infertile hyperprolactinimic women (patients), age ranged16-38 years old, and 56 normoprolactinemic women as a control group, 18-37 years old. Serum prolactin (PRL) and gonadotroph hormones (Follicle stimulating hormone FSH and Luteinizing hormone LH) were measured using enzymatic immunoassay (EIA) method, resorcinol method for serum total sialic acids (SIA). Patients were divided into four groups, each group represented the level of prolactin of infertile women as follow: G1= (21-30), G2= (31-40), G3= (41-50), and G4= (51-60) ng/mL. S

Age and BMI may be used to diagnosis of thyroid autoimmune disease. One hundred Iraqi women with age ranged from 18 to 60 years participate in this research, 50 of them were hypothyroidism patients, 30 were hyperthyroidism patients and the other 20 were euthyroidism served as controls. Blood samples were collected from the studied subjects to determine thyroid profile [free triiodothyronine (FT3), free tetraiodothyronine (FT4) and thyroid stimulating hormone (TSH)], thyroid antibodies [anti-thyroid peroxidase (anti-TPO), anti-thyroglobulin (anti-Tg), and anti-thyroid stimulating hormone receptor (anti-TSHR)], and levels of vitamin D (vit D), calcium (Ca), and phosphorus (P) using different analysis techniques. When the effect of age

العقم هو أحد المشاكل التي تواجه النساء والرجال. تعد السمنة واضطرابات مستوى الدهون، وكذلك مقاومة الأنسولين، من عوامل الخطر التي تسبب العقم، بالإضافة إلى العوامل الأخرى ذات الصلة. تهدف هذه الدراسة إلى معرفة تأثير السمنة واختلال توازن الدهون مع دراسة علاقة كل من ثنائي الببتيديل ببتيديز-4 وعامل نخر الورم-الفا لدى النساء المصابات بالعقم مقارنة بالنساء غير المصابات به، لتحديد مدى إمكانية اعتمادها كعوامل تشخي

Pregnancy and childbirth are physiological states characterized by sudden hormonal and immunologically described changes. The current study aimed to investigate the influence of maternal variables (age, previous abortion, placental position, and fetal position) on some physiological biomarkers, such as oxytocin (OT), prolactin (PRL), cortisol, and insulin growth factor 2 (IGF -2) and some immune biomarkers such as programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1) and interleukin 6 (IL-6) in Iraqi women undergoing caesarean section (CS). Blood samples were collected from 48 pregnant women in the age range (16-43 years) and serum was obtained to determine the levels of the above biomarkers. The effect of

Background: Several studies suggested that skeletal system is adversely affected by diabetes and is associated with increased risk of osteoporosis and fragility fractures  

Objectives: The study was a case-control study that designed to assess the level of bone turnover markers (BTMs) among patients with type 2 diabetes mellitus (T2DM) and to investigate the effect of body weight and diabetic control on the level of bone turnover

Type of the study: Cross- sectional study.

Methods: The present study included 100 postmenopausal women with type 2 diabetes mellitus. Sixty-six non-diabetic postmenopausal women were enrolled as a control. Fasting b

This study investigates the implementation of Taguchi design in the estimation of minimum corrosion rate of mild-steel in cooling tower that uses saline solution of different concentration. The experiments were set on the basis of Taguchi’s L16 orthogonal array. The runs were carried out under different condition such as inlet concentration of saline solution, temperature, and flowrate. The Signal-to- Noise ratio and ANOVA analysis were used to define the impact of cooling tower working conditions on the corrosion rate. A regression had been modelled and optimized to identify the optimum level for the working parameters that had been founded to be 13%NaCl, 35ᴼC, and 1 l/min. Also a confirmation run to establish the p

This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in