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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 Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Thu Aug 18 2016
Journal Name
Artificial Cells, Nanomedicine, And Biotechnology
Biosynthesis of silver nanoparticles from <i>Catharanthus roseus</i> leaf extract and assessing their antioxidant, antimicrobial, and wound-healing activities
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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Molecular Structure
Synthesis, characterization, DFT calculations, molecular docking, ADMET analysis and biological activity of Schiff base metal complexes against colon cancer cells
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Publication Date
Fri Nov 01 2024
Journal Name
Heliyon
Strength and Deformation of Encased Concrete Columns by I- Section Steel and I- Section GFRP Subjected to Different Load Conditions
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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Optimum Reinforcement Depth Ratio for Sandy Soil Enhancement to Support Ring Footing Subjected to a Combination of Inclined-Eccentric Load
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This work investigates the impacts of eccentric-inclined load on ring footing performance resting on treated and untreated weak sandy soil, and due to the reduction in the footing carrying capacity due to the combinations of eccentrically-inclined load, the geogrid was used as reinforcement material. Ring radius ratio and reinforcement depth ratio parameters were investigated. Test outcomes showed that the carrying capacity of the footing decreases with the increment in the eccentric-inclined load and footing radius ratio. Furthermore, footing tilt and horizontal displacement increase with increasing the eccentricity and inclination angle, respectively. At the same time, the increment in the horizontal displacement due t

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Fabrication and characterization of zinc oxide nanorods coated by graphene oxide ZnO-NR@GO as a potential hybrid material photocatalyst
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Hybrid architecture of ZnO nanorods/graphene oxide ZnO-NRs@GO synthesized by electrostatic self-assembly methods. The morphological, optical and luminescence characteristics of ZnO-NRs@GO and ZnO-NRs thin films have been described by FESEM, TEM, HRTEM, and AFM, which refers to graphene oxide have been coated ZnO-NRs with five layers. Here we synthesis ZnO-NRs@GO by simple, cheap and environmentally friendly method, which made it favorable for huge -scale preparation in many applications such as photocatalyst. ZnO-NRs@GO was applied as a photocatalyst Rodamin 6 G (R6G) dye from water using 532 nm diode laser-induced photocatalytic process. Overall degradation of R6G/ ZnO-NRs@GO was achieved after 90 minutes of laser irradiation while it ne

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Publication Date
Tue May 12 2026
Journal Name
Canadian Metallurgical Quarterly
Investigation of Te <sub>50</sub> Se <sub>50-x</sub> Sn <sub>x</sub> alloys’ structural and electrical characteristics
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Publication Date
Thu Mar 01 2018
Journal Name
Spectrochimica Acta Part A: Molecular And Biomolecular Spectroscopy
Application of dyes extracted from Alternanthera dentata leaves and Musa acuminata bracts as natural sensitizers for dye-sensitized solar cells
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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Molecular Structure
Synthesis, characterization, DFT calculations, molecular docking, ADMET analysis and biological activity of Schiff base metal complexes against colon cancer cells
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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Food Process Engineering
Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
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Abstract<sec><label></label><p>This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic></p></sec> ... Show More
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