Endothelin-1 (ET-1) is a potent vasoconstrictor hormone that has been identified as an important factor
responsible for the development of cardiovascular dysfunctions. ET-1 exerts its vasoconstrictor activity
through two pharmacologically distinct receptors, ETA and ETB that are found in vascular smooth muscle
cells (VSMCs) and the vasodilator activity through an ETB receptor located on endothelial cells. This study
aimed to show the impact of 1µM L-arginine (LA), 100µM tetrahydrobiopterin (BH4), and their combined
effect on ET-1 activity in both lead-treated and lead-untreated rat aortic rings. This means, investigating how
endothelial dysfunction reverses the role of nitric oxide precursor and cofa

This study aimed to compare the safety and efficacy of laser lithotripsy and pneumatic lithotripsy, the two most commonly used transurethral lithotripsy methods for treating bladder stones in children in Iraq. Between January 2013 and December 2016, 64 children with bladder stones were included in this prospective randomized study, after ethical committee approval and written consent from the children’s parents or caregivers were obtained. Patients were assigned randomly by computer software to two groups treated with either pneumatic cystolithotripsy or laser lithotripsy. A 9 Fr. semirigid ureteroscope was used to pass the lithotripter through and fragment the stone. A catheter of 8–12 Fr. was then introduced and kept in place

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Fresh water resources in terms of water quality is a crucial issue worldwide. In Egypt, the Nile River is the main source of fresh water in the country and monitoring its water quality is a major task on governments and research levels. In the present case study, the physical, chemical and algal distribution in Nile River was monitored over two seasons (winter and summer) in 2019. The aims of the study were to check the seasonal variation among the different water parameters and also to check the correlations between those parameters. Water samples were collected from the Nile in Cairo governorate in EGYPT. The different physiochemical and microbiological properties in water samples were assessed. The studied parameters were included: te

This study aimed to identify the employment of the social networking platform «Twitter» in the 2016 presidential campaign led by the Republican candidate, Donald Trump; and analyse his tweets through his personal account on «Twitter»  for the period from: 10/ 8/2016 to: 11/ 8/2016 which represents the last month of the election campaign.

The study belongs to the type of descriptive studies using the analytical method through an analysis index that includes sub-categories and other secondary categories. The research has adopted the ordinary unit of information material (tweet) as an analysis unit for this purpose.

The angiotensin converting enzyme (ACE) I\D gene polymorphism influences the blood ACE enzyme activity. Renoprotective effect of ACE inhibitors (ACEIs) varies among patients due to genetic variation, particularly in Renin-Angiotensin-Aldosterone System genes. This study investigates the genetic variations of ACE I\D and AGT1RA1166C gene polymorphisms in the antiproteinuric effect of ACEI therapy in type 2 diabetes mellitus (T2DM) patients. This is a cross-sectional study that included 76 T2DM patients who are ACEI users, divided into two groups: T2DM without diabetic kidney disease (DKD) included 31 patients, and T2DM with DKD included 45 patients. Urine samples were taken for measurement of urine albumin and creatinine, then calcul