Abstract Metabolic syndrome (MS) is a group of clinical and biological abnormalities included risk of insulin resistance , disorders in glucose metabolism , abdominal obesity and abnormal lipid profile these features confer a greater risk of cardiovascular diseases . Anyway, the co-occurrence of diabetes mellitus and metabolic syndrome potentiates the cardiovascular risk associated with each of the two conditions. The present study aimed to determine a relationship between prolactin level in type -2- diabetic Iraqi women and metabolic syndrome, as well to find a relationship between prolactin level and other studied biochemical markers. seventy menopausal diabetic women with metabolic syndrome with age in range (45-50) years were enrolled in this study , and were compared with matched age control group which consisted of menopausal women suffering from uncomplicated diabetic patients (without metabolic syndrome ). Two groups were not given any treatment , they were newly diagnosed. This study highlights the role of metabolic syndrome in the abnormalities of prolactin blood glucose , lipid profile , glycated hemoglobin and body mass index regardless the role of diabetic mellitus. Available evidence from the present study have reported that prolactin is a novel biochemical marker in sera of Iraqi menopausal type-2 diabetic women with metabolic syndrome . Moreover this study is the first highlights not only the association between lower level prolactin and metabolic syndrome in type-2 diabetic women but also the correlation between lower prolactin level and other biochemical markers ( Lipid profile , HbA1c and BMI ) in type-2- diabetic women with metabolic syndrome . Keywords : Prolactin . metabolic syndrome . type-2- diabetes mellitus . lipid prolile (PDF) Prolactin is a Novel Biochemical Marker in Sera of Iraqi Type-2 Diabetic Women With Metabolic Syndrome in Baghdad.. Available from: https://www.researchgate.net/publication/325257100_Prolactin_is_a_Novel_Biochemical_Marker_in_Sera_of_Iraqi_Type-2_Diabetic_Women_With_Metabolic_Syndrome_in_Baghdad [accessed Jun 06 2021].
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Background: Polycystic ovarian syndrome is a common endocrine disorder affecting 6-10% of women of reproductive age and the most common cause of anovulatory infertility. Objective: The aim of the study was to compare the effectiveness, side effects and outcomes of step-up gonadotrophin protocol versus laparoscopic ovarian diathermy (LOD) in infertile patients with clomiphene citrate resistant polycystic ovary syndrome. Methods: The sample included women who attended our infertility clinic at Al-Elwiya Maternity Teaching Hospital and Kamal Al-Samarraee for Infertility and IVF Hospital in Baghdad/ Iraq from November 2013 to November 2014. Eighty cases of infertile women with polycystic ovarian syndrome who failed t
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Background: Polycystic ovarian syndrome is a common endocrine disorder affecting 6-10% of women of reproductive age and the most common cause of anovulatory infertility.
Objective: The aim of the study was to compare the effectiveness, side effects and outcomes of step-up gonadotrophin protocol versus laparoscopic ovarian diathermy (LOD) in infertile patients with clomiphene citrate resistant polycystic ovary syndrome.
Methods: The sample included women who attended our infertility clinic at Al-Elwiya Maternity Teaching Hospital and Kamal Al-Samarraee for Infertility and IVF Hospital in Baghdad/ Iraq from November 2013 to November 2014. Eighty case
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Background: It is well known that oral carriage
of Candida species increase in many situations, like
obesity, debility, leukemia, viral infection, use of
certain drugs in addition to diabetes mellitus.
Objective: find the relation between diabetes and
its control on oral carriage of Candida.
Methods: Thirty four hundred oral swabs from
diabetic patients 67% are females and 33% are
males, 41.7% are type 1 diabetes and 58.3% are type
2.different culture media are used.
Results: we found that 37.9% of diabetics had oral
carriage, older age group had more but the
difference is not significant statistically P>0.05, in
addition females carry more Candida than males
P<0.05, while type of diabetes
Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
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