Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.
Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.
Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo
... Show MoreMany international studies indicated that the polymorphisms of some genes disturbed the folate homocysteine (Hcy) metabolism and increased the vulnerability to Down syndrome (DS). We aimed to measure the serum levels of folate and Hcy in DS children and compare the levels with age and sex-matched apparently normal healthy children. We also aimed to study the A80G polymorphism of the gene reduced folate carrier (RFC1) in the DS children as a risk factor. Forty children with DS (24 were boys, and 16 were girls) with the age range between 5-13 years, and 26 normal healthy children (16 boys and ten girls) were included in this study. The results show that the highest genotype in the control group was AG (53.85%) followed by AA and GG (30.
... Show MoreThe technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.
There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr
... Show MoreGiven the increasing global use of antibiotics, it has become necessary to examine and recognize their significance. An antibiotic formulation may contain one or more active components, depending on the antibiotic’s type and formulation. Antibiotics act exclusively against bacterial diseases and are ineffective against viral infections such as the common cold and influenza. The purpose of this review is to analyze the existing literature on the determination of antibiotics and to present the methods used for estimating specific antibiotics, including cephalexin, cloxacillin, piperacillin, nafcillin, and cefamandole, in medicinal preparations and biological fluids, such as blood and urine, from humans and animals. Verifying the quality of
... Show MoreAround 65 million individuals suffer from epilepsy worldwide, and when it is not properly treated, it is linked to higher rates of physical harm and mortality. Due to the requirement for long‐term therapy and the side effects of many medications, medication compliance is a significant issue. The purpose of this review was to summarize the findings of previous studies examining the quality of life (QOL), adherence, patient education, and medication knowledge, as well as the impact of a pharmacist‐led educational intervention. Additionally, to find out if these studies benefit epileptic patients, to find the appropriate method used to help them in all aspects of their lives, and to use these in future studies. A systematic and comprehensi
... Show MoreDeep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
... Show MoreCrabs belong to the crustacean family (Decapods crustacean), and their shells contain natural ingredients from which the bioactive compounds are derived. It has been used as folklore medicine in cancer treatment. We investigate the possible anti-inflammatory and anti-oxidant effects for crab shells and whole crabs. Thirty-six rats (150–200 gm) from both sexes were used, divided into six groups, the anti-inflammatory and anti-oxidant activity measured using cotton pellet induce granuloma model. Detection of tumor necrosis factor alpha (TNF α), Interleukin 1 beta (IL-1β), superoxide (SOD), and malondialdehyde (MDA) levels using ELISA Kits. The data analysis by one-way ANOVA followed by the Tukey test. Values are significant at (p < 0.05).
... Show More<p><strong>Objective: </strong>The aim of our study was to compare between flavonoids and phenolic acids contents of leaves and fruits of <em>Melia azedarach</em> since no phytochemical investigation had done previously in Iraq.</p><p><strong>Methods: </strong>The leaves and fruits of <em>Melia azedarach </em>were extracted by soxhlet using 80% ethanol then the dried extract was suspended in water and fractionated using petroleum ether, chloroform, ethyl acetate, and n-butanol. The n-butanol fraction was hydrolyzed by acid and partitioned with ethyl acetate. The different fractions containing flavonoids and phenolic acids were analyzed by HPLC and HPTLC.</p><
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