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Correlation with renin-angiotensin-aldosterone and glomerular filtration rate in chronic renal failure patients
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Background: One of the more significant hormonal systems, the renin-angiotensin-aldosterone system, controls the kidney function, adrenal gland through its effect on the balance of sodium and potassium, blood pressure, fluid volume, and also manages the functions of cardiovascular. Objective: To clarify the interrelationship between renal dysfunction and renin-angiotensin-aldosterone system. Patients and Methods: One hundred samples were collected from December 1, 2022, to February 18, 2023, from Al Shams Medical Laboratories (56 male, and 44) female, age range (of 45-60 years), all of them were volunteers suffering from chronic renal failure in the third stage the average glomerular filtration rate was 35. 70 ± 0.37 125 mL/min/1.73m2. and under conservative treatment. Kidney function test, active renin, angiotensin II, and aldosterone were assessed in the serum of all subjects. The p - value of differences less than 0.05 is measured significant, and uses the statistical package for the social sciences (23) software to calculate the correlation coefficient between various parameters. Results: The result shows relationship between the changes in GFR with creatinine, urea and active renin, the mean GFR showed significant negative correlated with mean creatinine (R = -0.76, p < 0.01. As well as the mean GFR with mean urea (R = -0.64, p < 0.01). The mean GFR also showed significant negative correlated with mean active renin in (R = -0.41, p < 0.01). Also, the mean serum active renin level was significantly positive correlated with mean aldosterone (R =0.33, p < 0.05). Conclusion: Renin enzyme is inversely related to renal dysfunction, so when the glomerular filtration rate decrease, the higher the renin increased, and as a result, the increase in blood pressure in chronic renal failure patients.

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Publication Date
Thu Jan 27 2022
Journal Name
Journal Of Population Therapeutics And Clinical Pharmacology
Is adding an Oral Antibiotic with the Topical Antibiotic-Steroid Useful in Treatment of Uncomplicated Acute Otitis Externa in Immunocompetent Patients?
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Publication Date
Fri Jan 13 2023
Journal Name
World Academy Of Sciences Journal
Potential effects of miR‑146 expression in relation to malondialdehyde as a biomarker for oxidative damage in patients with breast cancer
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Evaluation of Sex Hormone Levels in Benign Prostatic Hyperplasia Patients Treated with 5 Alpha-Reductase Inhibitor (Finasteride) in Amara city/Iraq
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The present study aimed to determine the serum sex hormone levels among Benign Prostatic Hyperplasia (BPH) patients before and after 3 months of oral administration of 5-α reductase inhibitor(finasteride). Forty BPH patients and 40 healthy men from Amara city were involved in this study, their ages were between 40-59 year. They were all subjected  to direct estimation of hormones by MinVidas method including Testosterone (T), Estradiol (E2), Follicle Stimulating Hormone (FSH), Luteinizing Hormone (LH), Prolactin (PRL), and Dihydrotestosterone (DHT) before and after 3 months of treatment with 5α-reductase inhibitor (finasteride) (the healthy individuals didn’t take finasteride).The results showed that T level was significantly lo

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Effects of various analgesics on pain perception and rate of tooth movement: a randomized controlled clinical study
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Background: Pain is one of the most reported side effects of orthodontic treatment despite the advanced technology in orthodontics. Many analgesics have been introduced to control orthodontic pain including acetaminophen and selective and nonselective nonsteroidal anti-inflammatory drugs. The great concern about these drugs is their adverse effect on rate of teeth movement. Aims: The purpose of this study was to evaluate and compare the effect of acetaminophen, ibuprofen and etoricoxib on pain perception and their influence on the rate of teeth movement during leveling and alignment stage. Methods: Forty patients were evenly and randomly distributed in a blinded way to one of four groups: placebo (starch capsules), acetaminophen 500mg th

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Parametric Analysis of Surface Roughness and Metal Removal Rate during Electrical Discharge Machining of O1 Tool Steel
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This work studies the impact of input machining parameters of Electrical Discharge Machining (EDM) on the machining process performance. Tool steel O1 was selected as the workpiece material, copper as the electrode material, and kerosene as the dielectric medium. Experimental runs have been carried out with a Design of Experiment (DOE) technique. Twenty tests are accomplished with the current range of (18 to 24 Ampere), a pulse duration range of (150 to 200 µs), and a pulse-off time range of (25 to 75 µs). Based upon the experimental study's output results, the EDM parameter's effect (voltage of power supply, discharge current, pulse duration, and pulse pause interval) on the responses of the process represented by sur

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Publication Date
Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
An Experimental Study on Electrochemical Grinding Parameters on Hardness and Material Removal Rate for Stainless Steel 316
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Electrochemical Grinding (ECG) process is a mechanically assisted electrochemical process for material processing. The process is able to successfully machine electrically conducting harder materials at faster rate with improved surface finish and dimensional control. This research studies the effect of applied current, electrolyte concentration, spindle speed and the gap between workpiece and tool on hardness and material removal rate during electrochemical grinding for stainless steel 316. The characteristic features of the electrochemical grinding process are explored through Taguchi-design-based experimental studies. The better hardness can be obtained at 10 A of the current, 150 g/l of the electrolyte concentration, 0.3 mm of gap an

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Assessment of Salivary Levels of the RANKL and RANK in Patients with Healthy Gingiva on Reduced Periodontium Versus Periodontitis: An Analytical Cross-Sectional Study
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Publication Date
Mon Jan 01 2024
Journal Name
Farmacia
ASSOCIATION OF NFE2L2 GENE POLYMORPHISM (rs35652124) WITH DEVELOPMENT OF RETINOPATHY IN IRAQI TYPE 2 DIABETIC PATIENTS, IN RELATION TO VASCULAR ENDOTHELIAL GROWTH FACTOR AND ENDOCAN SERUM LEVELS
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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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