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bsj-6104
Studying the genotype of Aryl Hydrocarbon Receptor-Interacting Protein (AIP) Gene (rs641081C>A) in ‎Iraqi Samples with Acromegaly Pituitary Adenoma
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Pituitary adenomas are the anterior pituitary tumors. Patients with an Aryl Hydrocarbon Receptor-Interacting Protein (AIP) mutation (AIP- mut) tend to have more aggressive tumors occurring at a younger age. Single nucleotide polymorphisms (SNPs) in many studies have been related to metabolic comorbidities in the general population. Study aims investigated the role of AIP gene SNPs with susceptibility to acromegaly pituitary- adenoma, with levels of LH, FSH, TSH, Testosterone, IGF1,GH, FT4 , Prolactin hormones and blood sugar levels.  The study ‎was conducted on a group of acromegaly patients, including 50 patients) both Genders( with ‎hyperplasia of the ends, and apparently healthy control group. Genotyping of AIP gene SNP (rs641081C >A‎) was indicated significant differences in frequency percentage between the study groups. The frequency of heterozygous CA genotype was significantly (p<0.01) higher in the patients' group when compared with control. The Means of IGF1, GH, prolactin, testosterone, and FBS were significantly ‎higher in patients at first treatment than that in control.‎ While,‎  the means of IGF1, GH, prolactin, and testosterone increased  significantly in patients at last treatment than control. Patients mean level of TSH decreased significantly at last ‎treatment. No significant differences (P ≥ 0.05) were detected between study ‎groups in all other values.‎ The Means of IGF1, GH, and prolactin at first and last treatment were significantly decreased, while LH ‎was significantly increased at last treatment. In ‎patients with heterozygous mutant and wild genotype, means of IGF1, GH, and ‎prolactin decreased significantly at last treatment compared ‎to first treatment. ‎In this study heterozygous rs641081C>A showed a risk factor for susceptibility of acromegaly. Also, serum IGF1, GH, prolactin, were affected by the SNP of AIP gene within carriers of genotypes of rs641081C>A.  IGF1, prolactin and GH ‎decreased significantly at last treatment compared to first treatment. 

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Publication Date
Thu Dec 05 2024
Journal Name
Anaesthesia, Pain &amp; Intensive Care
A comparative study between tongue thickness measured by ultrasonography and thyromental distance in anticipation of difficult intubation
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Background & objective: Difficult intubation remains a risk for patients undergoing general anesthesia (GA) or mechanical ventilation in an intensive care unit (ICU). Macroglossia is a known factor for difficult intubation. But it is not routine to assess the tongue size to predict difficult intubation. Studies are found deficient in comparing usefulness of measuring thyromental distance and the tongue thickness (TT) measured by ultrasonography to estimate difficult intubation. We compared tongue thickness measured by ultrasonography and thyromental distance as a means to anticipate difficult intubation. Methodology: A convenient sample of 60 patients; 32 males and 28 females, who were undergoing elective surgery with GA were i

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Publication Date
Sun Jan 01 2023
Journal Name
Open Veterinary Journal
Plasma-activated water application for detoxification of aflatoxin B1, ochratoxin A, and fumonisin B1 in poultry feeds
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Background: Plasma-activated water (PAW) is considered one of the emerging strategies that has been highlighted recently in the food industry for microbial decontamination and mycotoxin detoxification, due to its unique provisional characteristics. Aim: The effectiveness of PAW for aflatoxin B1 (AFB1), ochratoxin A (OTA), and fumonisin B1 (FB1) detoxification in naturally contaminated poultry feeds with its impacts on the feed quality were inspected. Methods: PAW-30 and PAW-60 were utilized for feed treatment for six time durations (5, 10, 15, 20, 40 and 60 min) each. The alterations in the physicochemical properties of PAW after different time durations of plasma inducement and treatment with and without feed samples were monit

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Publication Date
Mon Jan 01 2018
Journal Name
Pakistan Journal Of Medical & Health Sciences
Prevalence of Peripheral Arterial Disease in End Stage Renal Disease Patients Undergoing Hemodialysis: A Cross-Sectional Study
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The chronic renal disease is a principle common medical dilemma in Iraq. Peripheral arterial disease (PAD) is a prevalent infirmity in the hemodialysis people. The aim of present study was to estimate the prevalence of PAD in subjects with end-stage renal disease (ESRD). This cross-sectional study was done between January 2016 and May 2017 on ESRD subjects regularly attending renal dialysis unit in Al-Kindy teaching hospital in Baghdad, Iraq. PAD was diagnosed on the base of the ankle-brachial index (ABI) measured by using a hand-held Doppler ultrasound. Subjects with ABI ≤0.9 were supposed positive for PAD. A total of 150 ESRD cases were analyzed. The mean age of the subject was 49.52±15 years. Majority of them were males 87(58%). Most

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Medicine And Life
Renal stone density on native CT-scan as a predictor of treatment outcomes in shock wave lithotripsy
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Extracorporeal shock wave lithotripsy (ESWL) is considered a standard treatment for nephrolith or kidney stones measuring less than 20 mm. Anatomical, machine-related, and stone factors play pivotal roles in treatment outcomes, the latter being the leading role. This paper examined the relationship between stone density on native CT scans and ESWL treatment to remove renal stones concerning several treatments. One hundred and twenty patients (64 males and 56 females) were enrolled and completed the study from April 2019 to September 2020. Inclusion criteria were a single renal pelvis stone of 5–20 mm to be treated for the first time in adult patients with no urinary or musculoskeletal anatomical abnormalities. We assessed patients

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Publication Date
Sun Jan 01 2017
Journal Name
Proceeding Of Second Thermal And Fluids Engineering Conference
Solidification Enhancement in Triplex-Tube Latent Thermal Energy Storage System Using a Combination of Nanoparticles and Fins
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Publication Date
Mon Feb 01 2021
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Wed Oct 16 2019
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Depression, Anxiety and Stress Among a Sample of Chronic Hepatitis C Patients in AL-Najaf Province /Iraq
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Previous studies in Euro-American countries have shown that patients with chronic hepatitis C virus infection have increased levels of neuropsychiatric symptoms. While chronic hepatitis C virus infection has been reported in Arab countries such as Iraq, there is little studies about the neuropsychological burden associated with chronic hepatitis C among patients in the Arab region. The aim of the current study was to measure the prevalence and level of severity of depression, anxiety and stress among a sample of chronic hepatitis C patients in AL-Najaf province /Iraq. The current study was cross-sectional study carried out on (110) already diagnosed chronic viral hepatitis C patients who attended the Gastroenterology and Hepatology

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned

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Publication Date
Fri Dec 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A comparative study of Gaussian mixture algorithm and K-means algorithm for efficient energy clustering in MWSN
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Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

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