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Plasma Sclerostin Level in Multiple Myeloma
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Background:

Multiple myeloma (MM) is a heterogenous plasma cell malignancy with various complications. Sclerostin is a Wingless-type (Wnt) inhibitor specifically expressed by osteocytes; it acts as a negative regulator of bone formation.

Objectives:

To assess plasma sclerostin level in MM patients and find its correlations with clinical and laboratory data, including osteolytic bone disease and international staging system (ISS).

Materials and Methods:

This cross-sectional study included 80 individuals: 40 newly diagnosed MM patients and 40 healthy adults. Patients were divided according to the presence of bone disease and ISS stage and were investigated for complete blood count, blood film and bone marrow (BM). Plasma levels of β2-microglobulin and sclerostin were measured using competitive and sandwich enzyme immunoassay techniques, respectively.

Results:

Sclerostin level was significantly increased in MM patients than control group (P < 0.001) and was significantly higher in those with osteolytic bone disease and/or pathological fractures than those without bone lytic lesions (P < 0.001). Patients with ISS stage III showed significantly higher sclerostin level than stages I and II (P = 0.003). High sclerostin levels were positively correlated with blood urea, serum creatinine, uric acid, and β2-microglobulin (P-values 0.034, <0.001, <0.018 and <0.001, respectively) and negatively with glomerular filtration rate (P = 0.001). No significant correlation was found with age, gender, hematological and other biochemical parameters.

Conclusions:

In newly diagnosed MM patients, the plasma sclerostin was significantly correlated with renal impairment. High levels of plasma sclerostin were also found in advanced disease stage and with the presence of significant bone disease.

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measurement and accounting disclosure of intellectual capital using accounting models in the Iraqi insurance company
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The research aims to shed light on the possibility of measuring the intellectual capital in the Iraqi insurance company using accounting models, as well as disclosing it in the financial statements of the company, where human capital was measured using the present value factor model for discounted future revenues and the intellectual value-added factor model for measuring structural capital It was also disclosed in the financial statements based on the theory of stakeholders. The research problem lies in the fact that the Iraqi insurance company does not carry out the process of measuring and disclosing the intellectual capital while it is considered an important source for the company’s progress in the labor market recently. T

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Publication Date
Sun Apr 03 2011
Journal Name
لمؤتمر العلمي الرابع لكلية التربية/ جامعة سامراء
A comparison between alanine aminopeptidase (AAP) activity in type 2 diabetes and diabetic cardiac patients.
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Publication Date
Thu Jun 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of titanium dioxide nanoparticles on the activity of salivary peroxidase in periodontitis patients
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Background:The technology of nanoparticles has been expanded to many aspects of modern life. Titanium dioxide nanoparticles were of many nanomaterials utilized in biomedical applications. The interactions between nanoparticles and proteins are believed to be the base for the biological effect of the nanoparticles. The oxidation reaction of many substances is catalyzed by oxidizing enzymes called peroxidases. The activity of salivary peroxidase is elevated with periodontal diseases. the aim ofthis study is to examine the action of titanium dioxide nanoparticles on salivary peroxidase activity.Material and method75 participants were enrolled in this study—Periodontitis group with 44 participants and the non-periodontitis group with 31 pa

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Publication Date
Fri May 01 2009
Journal Name
Atti Della “fondazione Giorgio Ronchi”
Study of synthesis of nanocrystalline CdS thin film in PVA matrix by chemical bath deposition
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SUMMARY. – Nanocrystalline thin fi lms of CdS are deposited on glass substrate by chemical bath deposited technique using polyvinyl alcohol (PVA) matrix solution. Crystallite size of the nanocrystalline films are determining from broading of X-ray diffraction lines and are found to vary from 0.33-0.52 nm, an increase of molarity the grain size decreases which turns increases the band gap. The band gap of nanocrystalline material is determined from the UV spectrograph. The absorption edge and absorption coefficient increases when the molarity increases and shifted towards the lower wavelength.

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Fri Aug 15 2025
Journal Name
Iraqi Journal Of Agricultural Sciences
PURIFICATION OF PHYTASE PRODUCED FROM A LOCAL FUNGAL ISOLATE AND ITS APPLICATIONS IN FOOD SYSTEMS
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Publication Date
Thu Jan 30 2020
Journal Name
Neuroquantology
Studying Effect of Temperature on Electron Transport Parameter and Coefficients in CF3I Mixture with N2O
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Publication Date
Mon May 01 2017
Journal Name
2017 24th International Conference On Telecommunications (ict)
Load balancing by dynamic BBU-RRH mapping in a self-optimised Cloud Radio Access Network
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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