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Investigating the Effect of Genetic Polymorphisms of Deiodinase Type 2 on Levothyroxine Dose Requirements in Patients with Hypothyroidism
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Background: Hypothyroidism is the most abundant thyroid disorder worldwide. For decades, levothyroxine was the main effective pharmacological treatment for hypothyroidism. A variety of factors can influence levothyroxine dose, such as genetic variations. Studying the impact of genetic polymorphisms on the administration of medications was risen remarkably. Different genetic variations were investigated that might affect levothyroxine dose requirements, especially the deiodinase enzymes.  Deiodinase type 2 genetic polymorphisms’ impact on levothyroxine dose was studied in different populations.

Objective: To examine the association of the two single nucleotide polymorphism (SNP)s of deiodinase type 2 (rs225013 and rs225014) and levothyroxine dose requirements.

Subjects and Methods: A cross-sectional study was conducted at Baghdad Center for Nuclear Medicine and Radiation Therapy located in Baghdad/ Iraq, from March to June 2022. Based on levothyroxine dose, the enrolled patients were divided into two groups: low dose group < 1.7 µg/kg/day and high dose group ≥ 1.7 µg/kg. Then genotyping analysis was done for both groups of the study.

Results: The mean age of the participants was 40.35 ± 9.5 years with a mean body mass index of 30.61 ± 5.72 kg/m2. The mean levothyroxine doses in the low- and high-dose groups were 81.67 ± 30.74 µg/day and 161.67 ± 35.19 µg/day, respectively. Significant differences existed in the levels of TSH and TT4 between the study’s groups.

Conclusion: This study indicated that the differences in levothyroxine dose, TSH, TT4 and TT3 levels were not associated with the DIO2 rs225013. Similarly, the differences in TSH, TT3 and TT4 levels revealed a non-significant association with DIO2 rs225014 except for levothyroxine dose which was higher in the patients who carried the wild type allele (TT).

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Exponentially Fitted Diagonally Implicit EDITRK Method for Solving ODEs
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This paper derives the EDITRK4 technique, which is an exponentially fitted diagonally implicit RK method for solving ODEs . This approach is intended to integrate exactly initial value problems (IVPs), their solutions consist of linear combinations of the group functions  and  for exponentially fitting  problems, with  being the problem’s major frequency utilized to improve the precision of the method. The modified  method EDITRK4 is a new three-stage fourth-order exponentially-fitted diagonally implicit approach for solving IVPs with functions that are exponential as solutions. Different forms of -order ODEs must be derived using the modified system, and when the same issue is reduced to a  framework of equations that can be sol

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Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Techniques مجلة التقني
A STUDY OF SOME TECHNICAL AND ECONOMICAL PARAMETERS FOR MACHINERY UNIT (NEW HOLLAND &amp;DISC PLOW) BY USING THREE DIFFERENT TILT ANGLES دراسة بعض المؤشرات الفنية والأقتصادية للوحدة الميكنية (الجرار نيوهولاند مع المحراث القرصي الثلاثي القلاب) بأستخدام زوايا ميل مختلفة للأقراص
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Publication Date
Wed Dec 26 2018
Journal Name
Iraqi Journal Of Science
New Improved Heuristic Method for Solving Travelling Salesman Problem
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In this paper we will investigate some Heuristic methods to solve travelling salesman problem. The discussed methods are Minimizing Distance Method (MDM), Branch and Bound Method (BABM), Tree Type Heuristic Method (TTHM) and Greedy Method (GRM).

The weak points of MDM are manipulated in this paper. The Improved MDM (IMDM) gives better results than classical MDM, and other discussed methods, while the GRM gives best time for 5≤ n ≤500, where n is the number of visited cities.

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
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      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
مقارنة مقدرات بيز لدالة المعولية لتوزيع باريتو من النوع الاول باستعمال دوال معلوماتية مضاعفة مختلفة
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The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto  type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for

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