BACKGROUND: Many genetic factors are known to be related to osteoporosis, and currently the role of the glucagon-like peptide-1 receptor (GLP-1R) gene in bone health has been studied intensively. Some variation of this gene, such as rs1042044 and rs6458093, are known to be linked to metabolic diseases and lower bone mineral density, however their specific contribution to osteoporosis remains largely unexplored. Therefore, this study was conducted to investigate the combined genotypic effect of rs1042044 and rs6458093 as a genetic risk factor for osteoporosis in postmenopausal Iraqi women.METHODS: Blood samples from 75 osteoporosis patients and 75 healthy controls, aged 45-85, were collected. DNA was extracted, and a region of GLP-1R gene was amplified by polymerase chain reaction (PCR) and sequenced using the Sanger method to identify polymorphisms. Serum parathyroid hormone (PTH) levels were also measured with chemiluminescent immunoassay (CLIA) methods.RESULTS: Significant differences were observed for age, menopausal age, and PTH levels (p<0.001), but not for Body Mass Index (BMI). While individual SNPs (rs1042044 and rs6458093) showed no significant association with osteoporosis, a specific genotype combination of rs1042044 A and rs6458093 G was found to be a highly significant risk factor for the disease (OR=21.85, p=0.026). Linkage Disequilibrium analysis showed a D' value=0.85 and R²=0.45 between the two SNPs.CONCLUSION: Co-occurrence of the 'A' allele at rs1042044 and the 'G' allele at rs6458093 creates a highly susceptible genetic risk factor for osteoporosis, highlighting a potential novel biomarker for disease risk and providing a benchmark for future studies.KEYWORDS: osteoporosis, postmenopausal, GLP1R, PTH, SNPS
COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in
B3LYP/6-31G, DFT method was applied to hypothetical study the design of six carbon nanotube materials based on [8]circulene, through the use of cyclic polymerization of two and three molecules of [8]circulene. Optimized structures of [8]circulene have saddle-shaped. Design of six carbon nanotubes reactions were done by thermodynamically calculating (Δ S, Δ G and Δ H) and the stability of these hypothetical nanotubes depending on the value of HOMO energy level. Nanotubes obtained have the most efficient gap energy, making them potentially useful for solar cell applications.
Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degr
... Show MoreThis work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
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Objective(s): To evaluate the nurses` practices for children who diagnosed with febrile convulsion.
Methodology: A quantitative research, descriptive correlational design was used in this study, the study conducted on nurses who work in Al-Diwaniya Pediatrics Teaching Hospital-Iraq for Maternal and Children period from 12th September 2021 to 10th October 2022. A non- probability (convenience) sample has been applied to obtain the study goals. The study sample was (21) nurses who participate in the study. The study tool is composed of two parts: The first part is concerned with collection of nurses socio-demographic data obta
... Show MoreOne of the costliest problems facing the production of hydrocarbons in unconsolidated sandstone reservoirs is the production of sand once hydrocarbon production starts. The sanding start prediction model is very important to decide on sand control in the future, including whether or when sand control should be used. This research developed an easy-to-use Computer program to determine the beginning of sanding sites in the driven area. The model is based on estimating the critical pressure drop that occurs when sand is onset to produced. The outcomes have been drawn as a function of the free sand production with the critical flow rates for reservoir pressure decline. The results show that the pressure drawdown required to
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